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“Congenital Insensitivity to Pain” (CIPA, or congenital analgesia: CIPA hereafter) is an autosomal recessive disease (Indo, 2002) and was first observed in 1932 (Daneshjou, Jafarieh, and Raeeskarami, 2012). It is called a “congenital disorder” since it is present from birth. Since the disease is autosomal recessive, the closer the two parents are in relatedness, the more likely it is they will pass on a recessive disorder since they are more likely to have and pass on autosomal recessive mutations (Hamamy, 2012). First cousins, for example, 1.7-2.8% higher risk of having a child with an autosomal recessive disease (Teeuw et al, 2013). Consanguinity is common in North Africa (Anwar, Khyatti, and Hemminki, 2014) and the Bedouin have a high rate of this disease (Schulman et al, 2001; Lopez-Cortez et al, 2020; Singer et al, 2020). Three mutations in the TrkA (AKA NTRK1) have been shown to induce protein mis-folding which affect the function of the protein. Different mutations in the TrkA gene have been shown to have be associated with different disease outcomes (Franco et al, 2016). Since the mutated gene in question is needed for nerve growth factors, the pain signals cannot be transferred to the brain since there are hardly any of them there (Shin et al, 2016).
Individuals unfortunate enough to be inflicted with CIPA cannot feel pain. Whether it’s biting their tongues, feeling pain from extreme temperatures. People with CIPA have said that while they can feel the difference between extreme temperatures—hot and cold—they cannot feel the pain that is actually associated with the temperatures on their skin see (Schon et al, 2018). When they bump into things, they may not be aware of what happened and injuries may occur which heal incorrectly due to no medical attention and only noticing the fractures and other things that occur due to CIPA years later after they see doctors for what is possibly factors due to having the disease. People with CIPA are thought to be “dumb” because they constantly bump into things. But what is really happening is that, since they cannot feel pain, they have not learned that bumping into things could be damaging to their bodies, as pain is obviously an experience-dependent event. So these people learn, throughout their lives, to fake being in pain as to not draw suspicion to people who may not be aware of the condition. Children with the disease are thought, most of the time, to be victims of child abuse, but when it is discovered that the child who is thought to be a victim of abuse is inflicted with CIPA (van den Bosch et al, 2014; Amroh et al, 2020), treatments shift toward managing the disease.
About twenty percent of people with CIPA live until three years of age (Lear, 2011), while 20 percent of those who die at age 3 die from complications due to hyperpexia (an elevated body temperature over 106. degrees Fahrenheit) (Rosemberg, Marie, and Kliemann, 1994; Schulmann et al, 2001; Indo, 2002; Nabyev et al, 2018). Since they cannot feel the heat and get themselves to cool down, Due to a low life expectancy (many more live until about 25 years of age), this disease is really hard to study (Inoyue, 2007; Daneshjou, Jafarieh, and Raeeskarami, 2012). People hardly make it past that age since they either don’t feel the pain and do things that normal people, through experience, know not to do since we can feel pain and know to not do things that cause us pain and discomfort or they commit suicide since they have no quality of life due to damaged joints. Furthermore, since they cannot feel pain, people with this disease are more likely to self-mutilate since they cannot learn that self-mutilation causes pain (since pain is a deterrent for future action that may in fact cause pain to an individual). They also cannot sweat, meaning that control of the body temperature of one afflicted with CIPA is of utmost precedence (since they could overheat and die). Thus, these cases of deaths of individuals with CIPA do not occur due to CIPA per se, they occur due to, say, not feeling heat and then sweating while not attempting to regulate their body temperature and cool down (whether by naturally sweating due to being too hot or getting out of the extreme hot temperature causing the elevated body temperature). This is known as “hyperpyrexia” and this cause of death affects around 20 percent of CIPA patients (Sasnur, Sasnur, and Ghaus-ul, 2011). Furthermore, they are more likely to have thick, leathery skin and also show little muscular definition.
Not sweating is associated with CIPA and if one cannot sweat, one cannot have their body temperature regulated when they get too hot. So if they get too hot they cannot feel it and they will die of heat stroke. The disease, though, is rare, as only 17-60 people in America currently have it, while there are about 600 cases of the disease worldwide (Inoyue, 2007; Lear, 2011). This disease is quite hard to identify, but clinicians may be able to detect the presence of the disease through the following ways: Infants biting their lips, fingers, cheeks and not crying or showing any instance of being in pain after the event; repeated fractures in older children; a history of burns with no medical attention; observing that a child has many healed joint injuries and bone fractures without the child’s parents seeking medical care; observing that the patient does not react to hot or cold events (though they can say they can feel a difference between the two) they make errors in distinguishing in whether something is hot or cold (Indo, 2008).
Children who have this disease are at a higher risk of having certain kinds of bodily deformations, since they cannot feel the pain that would make them be hesitant to perform a certain action in the future. Due to this, people with this disease must constantly check themselves for cuts, abrasions, broken bones, etc to ensure that they cannot feel when they actually occur to them. They don’t cry, or show any discomfort, when experiencing what should be an event that would cause someone without CIPA to cry. CIPA-afflicted individuals are more likely to have bodily deformations since their joints and bones do not heal correctly after injury. This then leads to their walking and appearance to be affected. This is one of many reasons why the parents of people with CIPA must constantly check their children for signs of bodily harm or unintentional injuries. One thing that needs to be looked out for is what is termed Charcot joint—which is a degenerative joint disorder (Gucev et al, 2020).
A specific form of CIPA—called HSAN-IV—was discovered in a village in southern Finland called Vittangi, where it was traced to the founder of the village itself in the 1600s. Since the village was remote with such a small population, this meant that the only people around to marry and have children with were people who were closely related to each other. This, then, is the reason why this village in Finland has a high rate of people afflicted with this disease (Norberg, 2006; Minde, 2006). This, again, goes back to the above on consanguinity and autosomal recessive diseases—since CIPA is an autosomal recessive disease, one would reason that we would find it in populations that marry close relatives, either due to custom or population density.
Many features have been noted as showing that an individual is afflicted with CIPA: absent pain sensation from birth, the inability to sweat; and mental retardation, lower height and weight for their age (Safari, Khaledi, and Vojdani, 2011; Perez-Lopez et al, 2015). Children with CIPA have lower IQs than children without CIPA, so there is an inverse relationship between IQ and age; the older the age of the child with CIPA, the lower their IQ, while the reverse is true for individuals who are younger (Erez et al, 2010). One girl, for example. had a WISC-III IQ of 49, and she self-mutilated herself by picking at her nails until they were no longer there (Zafeirou et al, 2004). Another girl with CIPA was seen to have an IQ of 52, be afflicted with mental retardation, have a low birth weight, and was microcephalic (Nolano et al, 2000). Others were noted to have IQs in the normal range (Daneshjou, Jafarieh, and Raaeskarami, 2012). People with a specific form of this disease (HSN type II) were observed to have IQs in the normal range (though it is “caused by” a different set of genes than CIPA, HSN type IV; Kouvelas and Terzoglou, 1989). However, it has been noted that the cut-off of 70 for mental retardation is arbitrary (see Arvidsson and Granlund, 2016). While running a full gamut of tests on an individual thought to have CIPA, we can better attempt to ensure a higher quality of life in individuals afflicted with the disease. In sum, IQ scores of CIPA individuals do not reflect that the mutations in TrkA “cause” IQ scores; it is an outcome of a disrupted system (in this case, mutations on the TrkA gene).
There is currently no cure for this disease, and so, the only way to manage complications stemming from CIPA is to work on the injuries that occur to the joints that occur as they happen, to ensure that the individual has a good quality of life. Treatment for CIPA, therefore, is not actually curing the disease, but it is curing what occurs due to the disease (bone breaks, joint destruction), which would then heighten the quality of life of the person with CIPA (Nabiyev, Kara, and Aksoy, 2016). Naloxone may temporarily relieve CIPA (Rose et al, 2018), while others suggest treatments such as remifentanil (Takeuchi et al, 2018). We can treat outcomes that arise from the disease (like self-mutilation), but we cannot outright cure the disease itself (Daneshjou, Jafarieh, and Raaeskarami, 2012). The current best way to manage the disease is to identify the disease early in children and to do full-body scans of afflicted individuals to attempt to cure the by-products of the disease (such as limb/joint damage and other injuries). Maybe one day we can use gene therapy to help the afflicted, but for now, the best way forward is early identification along with frequent check-ups. By managing body temperature, having frequent check-ups, modifying the behavior of the child as to avoid injuries, wearing a mouth guard so they do not grind their teeth or bite their tongue, avoiding hot or cold environments or food, (Indo, 2008; Rose et al, 2018).
CIPA is a very rare—and very interesting—disease. By better understanding its aetiology, we can better help the extremely low number of people in the world who suffer from this disease.
An amputation is a preventative measure. It is done for a few reasons: To stop the spread of a gangrenous infection and to save more of a limb after there is no blood flow to the limb after a period of time. Other reasons are due to trauma and diabetes. Trauma, infection, and diabetes are leading causes of amputation in developing countries whereas in developed countries it is peripheral vascular disease (Sarvestani and Azam, 2013). Poor circulation to an affected limb leads to tissue death—when the tissue begins turning black, it means that there is no or low blood flow to the tissue, and to save more of the limb, the limb is amputated just above where the infection is. About 1.8 million Americans are living as amputees. After amputation, there is a phenomenon called “phantom limb” where amputees can “feel” their limb they previously had, and even feel pain to it, and it is very common in amputees; about 60-80 percent of amputees report “feeling” a phantom limb (see Collins et al, 2018; Kaur and Guan, 2018). The sensation can occur either immediately after amputation or years after. Phantom limb pain is neuropathic pain—a pain that is caused by damage to the somatosensory system (Subedi and Grossberg, 2011). Amputees even have shorter lifespans. When foot-amputation is performed due to uncontrolled diabetes, mortality ranges between 13-40 percent for year one, 35-65 percent for year 3, and 39-85 percent in year 5 (Beyaz, Guller, and Bagir, 2017).
Race and amputation
Amputation of the lower extremities are the most common amputations (Molina and Faulk, 2020). Minority populations are less likely to receive preventative care, such as preventative vascular screenings and care, which leads to them being more likely to undergo amputations. Such populations are more likely to suffer from disease of the lower extremities, and it is due to this that minorities undergo amputations more often than whites in America. Minorities in America—i.e., blacks and “Hispanics”—are about twice as likely as whites to undergo lower-extremity amputation (Rucker-Whitaker, Feinglass, and Pearce, 2003; Lowe and Tariman, 2008; Lefebvre and Lavery, 2011; Mustapha et al, 2017; Arya et al, 2018)—so it is an epidemic for black America. Blacks are even more likely to undergo repeat amputation (Rucker-Whitaker, Feinglass, and Pearce, 2003). In fact, here is a great essay chronicling the stories of some double-amputee black patients.
Why do blacks undergo amputations more often than whites? One answer is, of course: Physician bias. For example, after controlling for demographic, clinical, and chronic disease status, blacks were 1.7 times more likely than whites to undergo lower-leg amputations (Feinglass et al, 2005; Regenbogen et al, 2007; Lefebvre and Lavery, 2011). What is a cause of this is inequity in healthcare—note that “inequity” here means differences in care that are avoidable and unjust (Sudana and Blas, 2013).
Another reason is due to complications from diabetes. Blacks have higher rates of diabetes than whites (Rodriguez and Campbell, 2007) but see Signorello et al (2007). Muscle fiber differences between races (see also here). Differences in hours-slept between blacks and whites, too, could also explain the severity of the disease. But what could also be driving differences in diabetes between races is the fact that blacks are more likely than whites to live in “food swamps.” Food swamps are where it is hard to find nutritionally-dense food, whereas food deserts are areas where there is little access to healthy, nutritious food. In fact, a neighborhood being a food swamp is more predictive of obesity status of the population in the area than is its being a food desert (Cooksey-Stowers, Schwartz, and Brownell, 2017). Along with the slew of advertisements in that are directed to low-income neighborhoods (see Cassady, Liaw, and Miller, 2015), we can now see how such things like food swamps contribute to high hospitalization rates in low-income neighborhoods (Phillips and Rogriguez, 2019). These amputations are preventable—and so, we can say that there is a lack of equity in healthcare between races which leads to these different rates in amputation—before even thinking about physician bias. Amputation rates for blacks in the southeast can be almost seven times higher than other regions (Goodney et al, 2014).
Stapleton et al (2018: 644) conclude in their study on physician bias and amputation:
Our study demonstrates that such justifications may be unevenly applied across race, suggesting an underlying bias. This may reflect a form of racial paternalism, the general societal perception that minorities are less capable of “taking care of themselves,” even including issues related to health and disease management.23 Underlying bias may prompt more providers to consider amputation for minority patients. Furthermore, unlike in transplant surgery, there is currently no formal process for assessing patient compliance with treatment protocols or self-care in vascular surgery.24 Asking providers to make snap judgments about patient compliance, without a protocol for objective assessment, allows subconscious bias to influence patient care.
Physician bias is pervasive (Hoberman, 2012)—whether it is conscious or unconscious racial bias. Such biases can and do lead to outcomes that should not occur. By attempting to reduce disparities in healthcare that then lead to negative outcomes, we can then attempt to improve the quality of healthcare given to lower-income groups, like blacks. Such biases lead to negative health outcomes for blacks (such as the claim that blacks feel less pain than whites), and if they were addressed and conquered, then we could increase equity between groups until access to healthcare is equal—and physician bias is an impediment to access to equal healthcare due to the a priori biases that physicians may hold about certain racial/ethnic groups. Medical racism, therefore, drives a lot of the amputation differences between blacks and whites. Hospitals that are better equipped to offer revascularization services (attempting to save the limb by increasing blood flow to the affected limb) even had a higher rate of amputations in blacks when compared to whites (Durazzo, Frencher, and Gusberg, 2013).
For example. Mustapha et al (2017) write:
Compared to Caucasian patients, several studies have found that African-Americans with PAD are more likely to be amputated and less likely to have their lower limb revascularized either surgically or via an endovascular approach [3–9]. In an early analysis of data from acute-care hospitals in Florida, Huber et al. reported that the incidence of amputation (5.0 vs. 2.5 per 10,000) was higher and revascularization lower (4.0 vs. 7.1 per 10,000) among African-Americans compared to Caucasians, even though the incidence of any procedure for PAD was comparable (9.0 vs. 9.6 per 10,000) . Other studies have reported that the probability of undergoing a revascularization or angioplasty was reduced by 28–49 % among African-Americans relative to Caucasians [3 6]
Pro-white unconscious biases were also found among physicians, as Kandi and Tan (2020) note:
There is evidence of both healthcare provider racism and unconscious racial biases. Green et al. found significant pro-White bias among internal medicine and emergency medicine residents, while James SA supported this finding, indicating a “pro-white” unconscious bias in physician’s attitudes towards, and interactions with, patients [43,44]. In a survey assessing implicit and explicit racial bias by Emergency Department (ED) providers in care of NA children, it was discovered that many ED providers had an implicit preference for white children compared to those who identified as NA . Indeed, racism and stigmatization are identified as being many American Indians’ experiences in healthcare.
One major cause of the disparity is that blacks are not offered revascularization services at the same rate as whites. Holman et al (2011: 425) write:
Finally, given that patients’ decisions are necessarily confined to the options offered by their physicians, racial differences in limb salvage care might be attributable to differences in physician decision making. There are some data to suggest lower vein graft patency rates in black patients compared to whites.18,19 A patient’s race, therefore, may influence a vascular surgeon’s judgment about the efficacy of revascularization in preventing or delaying amputation. Similarly, a higher proportion of black patients in our sample were of low SES, which correlates with tobacco use,20-22 and we know that continued tobacco use increases the risk of lower extremity graft failure approximately three-fold.23 It is possible that a higher proportion of black patients in our sample were smokers who refused to quit, in which case vascular surgeons would be much less likely to offer them the option of revascularization. While Medicare data include an ICD-9 diagnosis code for tobacco use, the prevalence in our study sample was approximately 2%, suggesting that this code was grossly unreliable as a means of directly measuring and adjusting for tobacco use.
Smoking, of course, could be a reason why revascularization would not be offered to black patients. Though, as I have noted, smoking ads are more likely to be found in lower-income neighborhoods which increases the prevalence of smokers in the community.
With this, I am reminded of two stories I have seen on television programs (I watch Discovery Health a lot—so much so that I have seen most of the programs they show).
In Untold Stories of the ER, a man came in with his hand cut off. He refused medical care. He would not let the doctors attempt to sew his hand back on. Upon the police entering his home to check for evidence (where his hand was found), they searched his computer. It seems that he had a paraphilia called “acrotomophilia” which is where one is sexually attracted to people with amputations. Although he wanted it to be done to himself—he had inflicted the wound on himself. After the doctor tried to reason with the man to have his hand sewed back on, the man would not let up. He did not want his hand sewed back on. I wonder if, years down the line, the man regretted his decision.
In another program (Mystery Diagnosis), a man had said that as a young boy, he had seen a single-legged war veteran amputee. He said that ever since then, he would do nothing but think about becoming an amputee. He lived his whole life thinking about it without doing anything about it. He then went to a psychiatrist and spoke of his desire to become an amputee. After some time, he eventually flew to Taiwan and got the surgery done. He, eventually, found happiness since he had done what he always wanted to.
While these stories are interesting they speak to something deep in the minds of the individuals who mutilate themselves or get surgery to otherwise healthy limbs.
Blacks are more likely than whites to receive amputations in affected limbs than whites and are less likely to receive treatments that may be able to save the affected limb (Holman et al, 2011; Hughes et al, 2013; Minc et al, 2017; Massada et al, 2018). Physician bias is a large driver of this. So, to better public health, we then must attempt to mitigate these biases that physicians have that lead to these kinds of disparities in healthcare. Medical and other kinds of racism have led to this disparity in amputations between blacks and whites. Thus, to attempt to mitigate this disparity, blacks must get the preventative care needed in order to save the affected limb and not immediately go for amputation. Thankfully, such disparities have been noticed and work is being done to decrease said disparities.
So race is a factor in the decision on whether or not to amputate a limb, and blacks are less likely to receive revascularization services.
Unless you’ve been living under a rock since the new year, you have heard of the “coup attempt” at the Capitol building on Wednesday, January 6th. Upset at the fact that the election was “stolen” from Trump, his supporters showed up at the building and rushed it, causing mass chaos. But, why did they do this? Why the violence when they did not get their way in a fair election? Well, Michael Ryan, author of The Genetics of Political Behavior: How Evolutionary Psychology Explains Ideology (2020) has the answer—what he terms “rightists” and “leftists” evolved at two different times in our evolutionary history which, then, explains the trait differences between the two political parties. This article will review part of the book—the evolutionary sections (chapters 1-3).
EP and ideology
Explaining why individuals who call themselves “rightists and leftists” behave and act differently than the other is Ryan’s goal. He argues, at length, that the two parties have two different personality profiles. This, he claims, is due to the fact that the ancestors of rightists and leftists evolved at two different times in human history. He calls this “Trump Island” and “Obama Island”—apt names, especially due to what occurred last week. Ryan claims that what makes Trump different from, say, Obama, is that his ancestors evolved at a different place in a different time compared to Obama’s ancestors. He further claims using the Stanford Prison Experiment that “we may not all be capable of becoming Nazis, after all. Just some, and conservatives especially so” (pg 12).
In the first chapter he begins with the usual adaptationism that Evolutionary Psychologists use. Reading between the lines in his implicit claims, he is arguing that “rightists and leftists” are natural kinds—that is, they are *two different kinds of people.* He explains some personality differences between rightists and leftists and then says that such trait differences are “rooted in biology and governed by genes” (pg 17). Ryan then makes a strong adaptationist claim—that traits are due to adaptation to the environment (pg 17). What makes you and I different from Trump, he claims, is that our ancestors and his ancestors evolved in different places at different times where different traits would be imperative to survival. So, over time, different traits got selected-for in these two populations leading to the trait differences we see today. So each environment led to the fixation of different adaptive traits which explains the differences we see today between the two parties, he claims.
Ryan then shifts from the evolution of personality differences to… The evolution of the beaks of Darwin’s finches and Tibetan adaptation to high-altitude living (pg 18), as if the evolution of physical traits is anything like the evolution of psychological traits. His folly is assuming that these physical traits can then be likened to personality/mental traits. The ancestors of rightists and leftists, like Darwin’s finches Ryan claims, evolved on different islands in different moments of evolutionary time. They evolved different brains and different adaptive behaviors on the basis of the evolution of those different brains. Trump’s ancestors were authoritarian, and this island occurred early in human history “which accounts for why Trump’s behavior seems so archaic at times” (pg 18).
The different traits that leftists show in comparison to rightists is due to the fact that their island came at a different point in evolutionary time—it was not recent in comparison to the so-called archaic dominance behavior portrayed by Trump and other rightists. Ryan says that Obama Island was more crowded than Trump Island where, instead of scowling, they smiled which “forges links with others and fosters reciprocity” (pg 19). So due to environmental adversity, they had a more densely populated “island”—in this novel situation, compared to the more “archaic” earlier time—the small bands needed to cooperate, rather than fight with each other, to survive. So this, according to Ryan, explains why studies show more smiling behavior in leftists compared to rightists.
Some of our ancestors evolved traits such as cooperativeness the aided the survival of all even though not everyone acquired the trait … Eventually a new genotype or subpopulation emerged. Leftist traits became a permanent feature of our genome—in some at least. (pg 19-20)
So the argument goes: Differences between rightists and leftists show us that the two did not evolve at the same points in time since they show different traits today. Different traits were adaptive at different points in time, some more archaic, some more modern. Since Trump Island came first in our evolutionary history, those whose ancestors evolved there show more archaic behavior. Since Obama Island came first, they show newer, more modern behaviors. Due to environmental uncertainty, those on Obama Island had to cooperate with each other. The trait differences between these two subpopulations were selected for in their environment that they evolved in, which is why they are different today. Now today, this led to the “arguing over the future direction of our species. This is the origin of human politics” (pg 20).
Models of evolution
Ryan then discusses four models of evolution: (1) the standard model, where “natural selection” is the main driver of evolutionary change; (2) epigenetic models like Jablonka’s and Lamb’s (2005) in Evolution in Four Dimensions; (3) where behavioral changes change genes; and (4) where organisms have phenotypic plasticity and is a way for the organism to respond to sudden environmental changes. “Leftists and rightists“, writes Ryan, “are distinguished by their own versions of phenotypic plasticity. They change behavior more readily than rightists in response to changing environmental signals” (pg 29-30).
In perhaps the most outlandish part of the book, Ryan articulates one of my now-favorite just-so stories. The passage is worth quoting in-full:
Our direct ancestor Homo erectus endured for two million years before going extinct 400,000 years ago when earth temperatures dropped far below the norm. Descendants of erectus survived till as recently as 14,000 years ago in Asia. The round head and shovel-shaped teeth of some Asians, including Vladimir Putin, are an erectile legacy. Archeologists believe erectus was a mix of Ted Bundy and Adolf Hitler. Surviving skulls point to a life of constant violence and routine killing. Erectile skulls are thick like a turtle’s, and the brow’s are ridged for protection from potentially fatal blows. Erectus’ life was precarious and violent. To survive, it had to evolve traits such as vigilant fearfulness, prejudice against outsiders, bonding with kin allies, callousness toward victims, and a penchant for inflexible habits of life that were known to guarantee safety. It had to be conservative. 34 Archeologists suggest that some of our most characteristic conservative emotions such as nationalism and xenophobia were forged at the time of Homo erectus. 35 (pg 33-34)
It is clear that Ryan is arguing that rightists have more erectus-like traits whereas leftists have more modern, Sapiens traits. “The contemporary coexistence of a population with more “modern” traits and a population with more “archaic” traits came into being” (pg 37). He is implicitly assuming that the two “populations” he discusses are natural kinds and with his “modern” “archaic” distinction (see Crisp and Cook 2005 who argue against a form of this distinction) he is also implying that there is a sort of “progress” to evolution.
Twin studies, it is claimed, show “one’s genetically informed psychological disposition” (Hatemi et al, 2014); they “suggest that leftists and rightists are born not made” while a so-called “consensus has emerged amongst scientists: political behavior is genetically controlled and heritable” (pg 43). But, Beckway and Morris (2008), Charney (2008), and Joseph (2009; 2013) argue that twin studies can do no such thing due to the violation of the equal environments assumption (Joseph, 2014; Joseph et al, 2015). Thus, Ryan’s claims of the “genetic origins” of political behavior rest on studies that cannot prove or disprove “genetic causation” (Shulitziner, 2017)—but since the EEA is false we must discount “genetic causation” for psychological traits, not least because it is impossible for genes to cause/influence psychological traits (see argument (iii)).
The arguments he provides are a form of inference to best explanation (IBE) (Smith, 2016). However, this is how just-so stories are created: the conclusion is already in mind, and then the story is crafted using “natural selection” to explain how a trait came to fixation and why it currently exists today. The whole book is full of such adaptive stories. Claiming that we have the current traits we do in the distributions they are in in the “populations” because they were, at a certain point in our evolutionary history, adaptive which then led to the individuals with those traits passing on more of their genes, eventually leading to trait fixation. (See Fodor and Piattelli-Palmarini, 2010).
Ryan makes such outlandish claims such as “Rightists are more likely than leftists to keep their desks neat. If in the distant past you knew exactly where the weapons were, you could find them quickly and react to danger more effectively. 26” (pg 45). He talks about how “time-consuming and effort-demanding accuracy of perception [were] more characteristic of leftist cognition … leftist cognition is more reflective” while “rightist cognition is intuitive rather than reflective” (pg 47). Rightists being more likely to endorse the status quo, he claims, is “an adaptive trait when scarce resources made energy management essential to getting by” (pg 48) Rightist language, he argues, uses more nouns since they are “more concrete, an anxious personalities prefer concrete to abstract language because it favors categorial rigidity and guarantees greater certainty” while leftists “use words that suggest anxiety, anger, threats, certainty, resistance to change, power, security, and conformity” (pg 49). There is “a connection between archaic physiology and rightist moral ideology” (pg 52). Certain traits that leftists have were “adaptive traits [that] were suited to later stage human evolution” (pg 53). Ryan just cites studies that show differences between rightists and leftists and then uses some great leaps and mental gymnastics to try to mold the findings as being due to evolution in the two different time periods he describes in chapter 1 (Trump and Obama Island).
I have not read one page in this book that does not have some kind of adaptive just-so story attempting to explain certain traits/behaviors between rightists and leftists in evolutionary terms. Ryan uses the same kind of “reasoning” that Evolutionary Psychologists use—have your conclusion in mind first and then craft an adaptive story to explain why the traits you see today are there. Ryan outright says that “[t]raits are the result of adaptation to the environment” (pg 17), which is a rare—strong adaptationist—claim to make.
His book ticks off all of the usual EP things: strong adaptationism, just-so storytelling, the claim that traits were selected-for due to their contribution in certain environments at different points in time. The strong adaptationist claims, for example, are where he says that erectus’ large brow “are rigid for protection from potentially fatal blows” (pg 34). Such strong adaptationist claims imply that Ryan believes that all traits are the result of adaptation and that they, as a result, are still here today because they all serve a function in our evolutionary past. His arguments are, for the most part, all evolutionary and follow the same kinds of patterns that the usual EP arguments do (see Smith, 2016 for an explication of just-so stories and what constitutes them). Due to the problems with evolutionary psychology, his adaptive claims should be ignored.
The arguments that Ryan provides are not scientific and, although they give off a veneer of being scientific by invoking “natural selection” and adaptationism, they are anything but. It is just a long-winded explanation for how and why rightists and leftists—liberals and conservatives—are different and why they cannot change, since these differences are “encoded” into our genome. The implicit claim of the book, then, that rightists and leftists are two different—natural—kinds, lies on the false bed of EP and, therefore, the arguments provided in the book fail to sway anyone that does not believe such fantastic storytelling masquerading as science. While he does discuss other evolutionary theories, such as epigenetic ones from Jablonka and Lamb (2005), the book is largely strongly adaptationist using “natural selection” to explain why we still have the traits we do in different “populations” today.
‘Health inequalities are the systematic, avoidable and unfair differences in health outcomes that can be observed between populations, between social groups within the same population or as a gradient across a population ranked by social position.’ (McCartney et al, 2019)
Health inequities, however, are differences in health that are judged to be avoidable, unfair, and unjust. (Sudana and Blas, 2013)
Asking “Is X racist?” is the wrong question to ask. If X is factual, then making the claim cannot be racist (facts themselves cannot be racist). But, one can perform a racist action—either consciously or subconsciously—on the basis of a fact. Facts themselves cannot be racist, but one can use facts to be racist. One can hold a belief and the belief can be racist (X group is better than Y group at Z), but systemic racism would be the result (the outcome) of holding said belief. (Some examples of systemic racism can be found in Gee and Ford, 2011.) Someone who holds the belief that, say, whites are more “intelligent” than blacks or Jews are more “intelligent” than whites could be said to be racist—they hold a racist belief and are making an invalid inference based on a fact (blacks score 15 points lower in IQ tests compared to whites so blacks are less intelligent). Truth cannot be racist, but truth can be used to attempt to justify certain policies.
I have argued that we should ban IQ tests on the basis that, if we believe that the hereditarian hypothesis is true and it is false, then we can enact policies on the basis of false information. If we enact policies on the basis of false information, then certain groups may be harmed. If certain groups may be harmed, then we should ban whatever led to the policy in question. If the policy in question is derived from IQ tests, then IQ tests must be banned. This is one example on how we can use a fact (like the IQ gap between blacks and whites) and use that fact for a racist action (to shuttle those who perform under a certain expectation into certain remedial classes based on the fact that they score lower than some average value). Believing that X group has a higher quality of life, educational achievement, and life outcomes on the basis of IQ scores—or their genes—is a racist belief but this racist belief can then be used to perform a racist action.
I have also discussed different definitions of “racism.” Each definition discussed can be construed as having a possible action attached to it. Racism is an action—something that we perform on the basis of certain beliefs, motivated by “what can be” possible in the future. Beliefs can be racist; we can say that it is an ideology that one acts on that has real causes/consequences to people. Truth can’t be racist; people can can use the truth to perform and justify certain actions. Racism, though, can be said to be a “cultural and structural system” that assigns value based on race; further, actions and intent of individuals are not necessary for structural mechanisms of racism (e.g., Bonilla-Silva, 1997).
We can, furthermore, use facts about differences between races in health outcomes and say that certain rationalizations of certain outcomes can be construed as racist. “It’s in the genes!” or similar statements could be construed as racist, since it implies that certain inequalities would be “immutable” on the basis of a strong genetic determination of disease.
Racism is indeed a public health issue. For instance, physicians can hold biases on race—just like the average person. For instance, differences in healthcare between majority and minority populations can said to be systemic in nature (Reschovsky and O’Malley, 2008). This needs to be talked about since racism can and is a determinant of health—as many places in the country are beginning to recognize. Racism is rightly noted as a public health crisis because it leads to disparate outcomes between whites and blacks based on certain assumptions on the ancestral background of both groups.
Quach et al (2012) showed that not receiving referrals to a specialist is discriminatory—Asians, too were also exposed to medical discrimination, along with blacks. Such discrimination can also lead to accelerated cellular aging (on the basis of measured telomere lengths where shorter telomeres indicate a higher biological compared to chronological age; Shammas et al, 2012) in black men and women (Geronimus et al, 2006; 2011; Schrock et al, 2017; Forrester et al, 2019). We understand the reasons why such discrimination on the basis of race happens, and we understand the mechanism by which it leads to adverse health outcomes between races (chronic elevation in allostatic load leading to higher than normal levels of certain stress hormones which will, eventually, lead to differences in health outcomes).
The idea that genes or behavior lead to differences in health outcomes is racist (Bassett and Graves, 2018). This can then lead to racist actions—that their genetic constitution impedes them from being “near-par” with whites, or that their behavior is the cause of the health disparities (sans context). Valles (2018: 186) writes:
…racism is a cause with devastating health effects, but it manifests via many intermediary mechanisms ranging from physician implicit biases leading to over-treatment, under-treatment and other clinical errors (Chapman et al. 2013; Paradies et al. 2015) to exposing minority communities to waterborne contaminants because of racist political disenfranchisement and neglect of community infrastructure (e.g., the infamous Flint Water Crisis afflicting my Michigan neighbors) (Krieger 2016; Sherwin 2017; Michigan Civil Rights Commission 2017).
There is a distinction between “equity” and “equality.” For instance, to continue with the public health example, take public health equality and public health equity. In this instance, “equality” means giving everyone the same thing whereas “equity” means giving individuals what they need to be the healthiest individual they can possibly be. “Strong equality of health” is “where every person or group has equal health“, while weak health equity “states that every person or group should have equal health except when: (a) health equality is only possible by making someone less healthy, or (b) there are technological limitations on further health improvement” (Norheim and Asada, 2009). But we should not attempt to “level-down” people’s health to achieve equity; we should attempt to “level up” people’s health, though. That is, it is impossible to reach a strong health equality (making all groups equal), but we should—and indeed, have a moral responsibility to—attempt to lift up those who are worse-off. Poverty is what is objectionable, inequality is not. It is impossible to achieve true equality between groups, but we can—and indeed we have a moral obligation to—lift up those who are in poverty, which is, also a social determinant of health (Braveman and Gottlieb, 2014; Frankfurt, 2015; Islam, 2019).
We achieve health equity when all individuals have the same access to be the healthiest individuals they can be; we achieve health equality when all health outcomes are the same for all groups. Health equity is, further, the absence of avoidable differences between different groups (Evans, 2020). One of these is feasible, the other is not. But racism does not allow us to achieve health equity.
The moral foundation for public health thus rests on general obligations in beneficence to promote good health. (Powers and Faden, 2006: 24)
Social justice is not only a matter of how individuals fare, but also about how groups fare relative to one another whenever systemic racism is linked to group membership. (Powers and Faden, 2006: 103)
…inequalities in well-being associated with severe poverty are inequalities of the highest moral urgency. (Powers and Faden, 2006: 114)
Public health is directly a matter of social justice. If public health is directly a matter of social justice, and if health outcomes due to discrimination are caused by social injustice, then we need to address the causes of such inequalities, which would be for example, conscious or unconscious prejudice against certain groups.
Certain inequalities between groups are, therefore, due to systemic racism which is an action which can be conscious or unconscious. But which inequalities matter most? In my view, the inequalities that matter most are inequalities that impede an individual or a group from having a certain quality of life. Racism can and does lead to health inequalities and by addressing the causes for such actions, we can then begin to ameliorate the causes of structural racism. This is more evidence that the social can indeed manifest in biology.
Holding certain beliefs can lead to certain actions that can be construed as racist and negatively impact health outcomes for certain groups. By committing ourselves to a framework of social just and health, we can then attempt to ameliorate inequities between social class/races, etc. that have plagued us for decades. We should strive for equity in health, which is a goal of social justice. We should not believe that such differences are “innate” and that there is nothing that we can do about group differences (some of which are no doubt caused by systemically racist policies). Health equity is something we should strive to do and we have a moral obligation to do so; health equality is not obligatory and it is not even a feasible idea.
If we can avoid health certain outcomes for certain groups on the basis of beliefs that we hold, then we should do so.
The use of polygenic scores has caused much excitement in the field of socio-genomics. A polygenic score is derived from statistical gene associations using what is known as a genome-wide association study (GWAS). Using genes that are associated with many traits, they propose, they will be able to unlock the genomic causes of diseases and socially-valued traits. The methods of GWA studies also assume that the ‘information’ that is ‘encoded’ in the DNA sequence is “causal in terms of cellular phenotype” (Baverstock, 2019).
For instance it is claimed by Robert Plomin that “predictions from polygenic scores have unique causal status. Usually correlations do not imply causation, but correlations involving polygenic scores imply causation in the sense that these correlations are not subject to reverse causation because nothing changes the inherited DNA sequence variation.”
Take the stronger claim from Plomin and Stumm (2018):
GPS are unique predictors in the behavioural sciences. They are an exception to the rule that correlations do not imply causation in the sense that there can be no backward causation when GPS are correlated with traits. That is, nothing in our brains, behaviour or environment changes inherited differences in DNA sequence. A related advantage of GPS as predictors is that they are exceptionally stable throughout the life span because they index inherited differences in DNA sequence. Although mutations can accrue in the cells used to obtain DNA, like any cells in the body these mutations would not be expected to change systematically the thousands of inherited SNPs that contribute to a GPS.
This is a strange claim for two reasons.
(1) They do not, in fact, imply causation since the scores derived from GWA studies which are associational and therefore cannot show causes—GWA studies are pretty much giant correlational studies that scan the genomes of hundreds of thousands of people and look for genes that are more likely to be in the sample population for the disease/”trait” in question. These studies are also heavily skewed to European populations and, even if they were valid for European populations (which they are not), they would not be valid for non-European ethnic groups (Martin et al, 2017; Curtis, 2018; Haworth et al, 2018).
(2) The claim that “nothing changes inherited DNA sequence variation” is patently false; what one experiences throughout their lives can most definitely change their inherited DNA sequence variation (Baedke, 2018; Meloni, 2019).
But, as pointed out by Turkheimer, Plomin and Stumm are assuming that no top-down causation exists (see, e.g., Ellis, Noble, and O’Connor, 2011). We know that both top-down (downward) and bottom-up (upward) causation exists (e.g., Noble, 2012; see Noble 2017 for a review). Plomin, it seems, is coming from a very hardline view of genes and how they work. A view, it looks like to me, that derives from the Darwinian view of genes and how they ‘work.’
Such work also is carried out under the assumption that ‘nature’ and ‘nurture’ are independent and can therefore be separated. Indeed, the title of Plomin’s 2018 book Blueprint implies that DNA is a blueprint. In the book he has made the claim that DNA is a “fortune-teller” and that things like PGSs are “fortune-telling devices” (Plomin, 2018: 6). PGSs are also carried out based on the assumption that the heritability estimates derived from twin/family/adoption studies tell us anything about how “genetic” a trait is. But, since the EEA is false (Joseph, 2014; Joseph et al, 2015) then we should outright reject any and all genetic interpretations of these kinds of studies. PGS studies are premised on the assumption that the aforementioned twin/adoption/family studies show the “genetic variation” in traits. But if the main assumptions are false, then their conclusions crumble.
Indeed, lifestyle factors are better indicators of one’s disease risk compared to polygenic scores, and so “This means that a person with a “high” gene score risk but a healthy lifestyle is at lower risk than a person with a “low” gene score risk and an unhealthy lifestyle” (Joyner, 2019). Janssens (2019) argues that PRSs (polygenic risk scores) “do not ‘exist’ in the same way that blood pressure does … [nor do they] ‘exist’ in the same way clinical risk models do …” Janssens and Joyner (2019) also note that “Most [SNP] hits have no demonstrated mechanistic linkage to the biological property of interest. By showing mechanistic relations between the proposed gene(s) and the disease phenotype, researchers would, then, be on their way to show “causation” for PGS/PRS.
Nevertheless, Sexton et al (2018) argue that “While research has shown that height is a polygenic trait heavily influenced by common SNPs [7–12], a polygenic score that quantifies common SNP effect is generally insufficient for successful individual phenotype prediction.” Smith-Wooley et al (2018) write that “… a genome-wide polygenic score … predicts up to 5% of the variance in each university success variable.” But think about the words “predicts up to”—this is a meaningless phrase. Such language is, of course, causal when they—nor anyone else—has shown that such scores are indeed casual (mechanistically).
What these studies are indexing are not causal genic variants for disease and other “traits”, they are showing the population structure of the population sampled in question (Richardson, 2017; Richardson and Jones, 2019). Furthermore, the demographic history of the sample in question can also mediate the stratification in the population (Zaidi and Mathieson, 2020). Therefore, claims that PGSs are causal are unfounded—indeed, GWA studies cannot show causation. GWA studies survive on the correlational model—but, as has been shown by many authors, the studies show spurious correlations, not the “genetics” of any studied “trait” and they, therefore, do not show causation.
One further nail-in-the-coffin for hereditarian claims for PGS/PRS and GWA studies is due to the fact that the larger the dataset (the larger the number of datapoints), there will be many more spurious correlations found (Calude and Longo, 2017). When it comes to hereditarian claims, this is relevant to twin studies (e.g., Polderman et al, 2015) and GWA studies for “intelligence” (e.g., Sniekers et al, 2017). It is entirely possible, as is argued by Richardson and Jones (2019) that the results from GWA studies “for intelligence” are entirely spurious, since the correlations may appear due to the size of the dataset, not the nature of it (Calude and Longo, 2017). Zhou and Zao (2019) argue that “For complex polygenic traits, spurious correlation makes the separation of causal and null SNPs difficult, leading to a doomed failure of PRS.” This is troubling for hereditarian claims when it comes to “genes for” “intelligence” and other socially-valued traits.
How can hereditarians show PGS/PRS causation?
This is a hard question to answer, but I think I have one. The hereditarian must:
(1) provide a valid deductive argument, in that the conclusion is the phenomena to be explained; (2) provide an explanans (the sentences adduced as the explanation for the phenomenon) that has one lawlike generalization; and (3) show the remaining premises which state the preceding conditions have to have empirical content and they have to be true.
An explanandum is a description of the events that need explaining (in this case, PGS/PRS) while an explanans does the explaining—meaning that the sentences are adduced as explanations of the explanans. Garson (2018: 30) gives the example of zebra stripes and flies. The explanans is Stripes deter flies while the explanandum is Zebras have stripes. So we can then say that zebras have stripes because stripes deter flies.
Causation for PGS would not be shown, for example, by showing that certain races/ethnies have higher PGSs for “intelligence”. The claim is that since Jews have higher PGSs for “intelligence” then it follows that PGSs can show causation (e.g., Dunkel et al, 2019; see Freese et al, 2019 for a response). But this just shows how ideology can and does color one’s conclusions they glean from certain data. That is NOT sufficient to show causation for PGS.
PGSs cannot, currently, show causation. The studies that such scores are derived from fall prey to the fact that spurious correlations are inevitable in large datasets, which also is a problem for other hereditarian claims (about twins and GWA studies for “intelligence”). Thus, PGSs do not show causation and the fact that large datasets lead to spurious correlations means that even by increasing the number of subjects in the study, this would still not elucidate “genetic causation.”