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The New York Times published an article on December the 8th titled What Doctors Should Ignore: Science has revealed how arbitrary racial categories are. Perhaps medicine will abandon them, too. It is an interesting article and while I do not agree with all of it, I do agree with some.
It starts off by talking about sickle cell anemia (SCA) and how was once thought of as a ‘black disease’ because blacks were, it seemed, the only ones who were getting the disease. I recall back in high-school having a Sicilian friend who said he ‘was black’ because Sicilians can get SCA which is ‘a black disease’, and this indicates ‘black genes’. However, when I grew up and actually learned a bit about race I learned that it was much more nuanced than that and that whether or not a population has SCA is not based on race, but is based on the climate/environment of the area which would breed mosquitoes which carry malaria. SCA still, to this day, remains a selective factor in the evolution of humans; malaria selects for the sickle cell trait (Elguero et al, 2015).
This is a good point brought up by the article: the assumption that SCA was a ‘black disease’ had us look over numerous non-blacks who had the sickle cell trait and could get the help they needed, when they were overlooked due to their race with the assumption that they did not have this so-called ‘black disease’. Though it is understandable why it got labeled ‘a black disease’; malaria is more prevalent near to the equator and people whose ancestors evolved there are more likely to carry the trait. In regards to SCA, it should be known that blacks are more likely to get SCA, but just because someone is black does not automatically mean that it is a foregone conclusion that one has the disease.
The article then goes on to state that the push to excise race from medicine may undermine a ‘social justice concept’: that is, the want to rid the medical establishment of so-called ‘unconscious bias’ that doctors have when dealing with minorities. Of course, I will not discount that this doesn’t have some effect—however small—on racial health disparities but I do not believe that the scope of the matter is as large as it is claimed to be. This is now causing medical professionals to integrate ‘unconscious bias training’, in the hopes of ridding doctors of bias—whether conscious or not—in the hopes to ameliorate racial health disparities. Maybe it will work, maybe it will not, but what I do know is that if you know someone’s race, you can use it as a roadmap to what diseases they may or may not have, what they may or may not be susceptible to and so on. Of course, only relying on one’s race as a single data point when you’re assessing someone’s possible health risks makes no sense at all.
The author then goes on to write that the terms ‘Negroid, Caucasoid, and Mongoloid’ were revealed as ‘arbitrary’ by modern genetic science. I wouldn’t say that; I would say, though, that modern genetic science has shown us the true extent of human variation, while also showing that humans cluster into 5 distinct geographic categories, which we can call ‘race’ (Rosenberg et al, 2002; but see Wills, 2017 for alternative view that the clusters identified by Rosenberg et al, 2002 are not races. I will cover this in the future). The author then, of course, goes on to use the continuum fallacy stating that since “there are few sharp divides where one set of traits ends and another begins“. A basic rebuttal would be, can you point out where red and orange are distinct? How about violet and blue? Blue and Cyan? Yellow and orange? When people commit the continuum fallacy then the only logical conclusion is that if races don’t exist because there are “few sharp divides where one set of traits ends and another begins“, then, logically speaking, colors don’t exist either because there are ‘few [if any] sharp divides‘ where one color ends and another begins.
The author also cites geneticist Sarah Tishkoff who states that the human species is too young to have races as we define them. This is not true, as I have covered numerous times. The author then cites this study (Ng et al, 2008) in which Craig Venter’s genome was matched with the (in)famous [I love Watson] James Watson and focused on six genes that had to do with how people respond to antipsychotics, antidepressants, and other drugs. It was discovered that Venter had two of the ‘Caucasian’ variants whereas Watson carried variants more common in East Asians. Watson would have gotten the wrong medicine based on the assumption of his race and not on the predictive power of his own personal genome.
The author then talks about kidney disease and the fact that blacks are more likely to have it (Martins, Agodoa, and Norris, 2012). It was assumed that environmental factors caused the disparity of kidney disease in blacks when compared to whites, however then the APOL1 gene variant was discovered, which is related to worse kidney outcomes and is in higher frequencies in black Americans, even in blacks with well-controlled blood pressure (BP) (Parsa et al, 2013). The author then discusses that black kidneys were seen as ‘more prone to failure’ than white kidneys, but this is, so it’s said, due to that one specific gene variant and so, race shouldn’t be looked at in regards to kidney disease but individual genetic variation.
In one aspect of the medical community can using medicine based on one’s race help: prostate cancer. Black men are more likely to be afflicted with prostate cancer in comparison to whites (Odedina et al, 2009; Bhardwaj et al, 2017) with it even being proposed that black men should get separate prostate screenings to save more lives (Shenoy et al, 2016). Then he writes that we still don’t know the genes responsible, however, I have argued in the past that diet explains a large amount—if not all of the variance. (It’s not testosterone that causes it like Ross et al, 1986 believe).
The author then discusses another medical professional who argues that racial health disparities come down to the social environment. Things like BP could—most definitely—be driven by the social environment. It is assumed that the darker one’s skin is, the higher chance they have to have high BP—though this is not the case for Africans in Africa so this is clearly an American-only problem. I could conjure up one explanation: the darker the individual, the more likely he is to believe he is being ‘pre-judged’ which then affects his state of mind and has his BP rise. I discussed this shortly in my previous article Black-White Differences in Physiology. Williams (1992) reviewed evidence that social, not genetic, factors are responsible for BP differences between blacks and whites. He reviews one study showing that BP is higher in lower SES, darker-skinned blacks in comparison to higher SES blacks whereas for blacks with higher SES no effect was noticed (Klag et al, 1991). Sweet et al (2007) showed that for lighter-skinned blacks, as SES rose BP decreased while for darker-skinned blacks BP increased as SES did while implicating factors like ‘racism’ as the ultimate causes.
There is evidence for the effect of psychosocial factors and BP (Marmot, 1985). In a 2014 review of the literature, Cuffee et al (2014) identify less sleep—along with other psychosocial factors—as another cause of higher BP. It just so happens that blacks average about one hour of sleep less than whites. This could cause a lot of the variation in BP differences between the races, so clearly in the case of this variable, it is useful to know one’s race, along with their SES. Keep in mind that any actual ‘racism’ doesn’t have to occur; the person only ‘needs to perceive it’, and their blood BP will rise in response to the perceived ‘racism’ (Krieger and Sidney, 1996). Harburg et al (1978) write in regards to Detroit blacks:
For 35 blacks whose fathers were from the West Indies, pressures were higher than those with American-born fathers. These findings suggest that varied gene mixtures may be related to blood pressure levels and that skin color, an indicator of possible metabolic significance, combines with socially induced stress to induce higher blood pressures in lower class American blacks.
Langford (1981) shows that when SES differences are taken into account that the black-white BP disparity vanishes. So there seems to be good evidence for the hypothesis that psychosocial factors, sleep deprivation, diet and ‘perceived discrimination’ (whether real or imagined) can explain a lot of this gap so race and SES need to be looked at when BP is taken into account. These things are easily changeable; educate people on good diets, teach people that, in most cases, no, people are not being ‘racist’ against you. That’s really what it is. This effect holds more for darker-skinned, lower-class blacks. And while I don’t deny a small part of this could be due to genetic factors, the physiology of the heart and how BP is regulated by even perceptions is pretty powerful and could have a lot of explanatory power for numerous physiological differences between races and ethnic groups.
Krieger (1990) states that in black women—not in white women—“internalized response to unfair treatment, plus non-reporting of race and gender discrimination, may constitute risk factors for high blood pressure among black women“. This could come into play in regards to black-white female differences in BP. Thomson and Lip (2005) show that “environmental influence and psychosocial factors may play a more important role than is widely accepted” in hypertension but “There remain many uncertainties to the relative importance and contribution of environmental versus genetic influences on the development of blood pressure – there is more than likely an influence from both. However, there is now evidence to necessitate increased attention in examining the non-genetic influences on blood pressure …” With how our physiology evolved to respond to environmental stimuli and respond in real time to perceived threats, it is no wonder that these types of ‘perceived discrimination’ causes higher BP in certain groups with lower SES.
Wilson (1988) implicates salt as the reason why blacks have higher BP than whites. High salt intake could affect the body’s metabolism by causing salt retention which influences blood plasma volume, cardiac output. However, whites have a higher salt intake than blacks, but blacks still ate twice the recommended amounts from the dietary guidelines (all ethnic subgroups they analyzed from America over-consumed salt as well) (Fulgoni et al, 2014). Blacks are also more ‘salt-sensitive’ than whites (Sowers et al 1988; Schmidlin et al, 2009; Sanada, Jones, and Jose, 2014) which is also heritable in blacks (Svetke, McKeown, and Wilson, 1996). A slavery hypothesis does exist to explain higher rates of hypertension in blacks, citing salt deficiency in the parts of Africa that supplied the slaves to the Americas, to the trauma of the slave trade and slavery in America. However, historical evidence does not show this to be the case because “There is no evidence that diet or the resulting patterns of disease and demography among slaves in the American South were significantly different from those of other poor southerners” (Curtin, 1992) whereas Campese (1996) hypothesizes that blacks are more likely to get hypertension because they evolved in an area with low salt.
The NYT article concludes:
Science seeks to categorize nature, to sort it into discrete groupings to better understand it. That is one way to comprehend the race concept: as an honest scientific attempt to understand human variation. The problem is, the concept is imprecise. It has repeatedly slid toward pseudoscience and has become a major divider of humanity. Now, at a time when we desperately need ways to come together, there are scientists — intellectual descendants of the very people who helped give us the race concept — who want to retire it.
Race is a useful concept. Whether in medicine, population genetics, psychology, evolution, physiology, etc it can elucidate a lot of causes for differences between races and ethnic groups—whether or not they are genetic or psychosocial in nature. That just attests to both the power of suggestion along with psychosocial factors in regards to racial differences in physiological factors.
Finally let’s see what the literature says about race in medicine. Bonham et al (2009) showed that both black and white doctors concluded that race is medically relevant but couldn’t decide why however they did state that genetics did not explain most of the disparity in relation to race and disease aside from the obvious disorders like Tay Sachs and sickle cell anemia. Philosophers accept the usefulness of race in the biomedical sciences (Andreason, 2009; Efstathiou, 2012; Hardimon, 2013; Winther, Millstein, and Nielsen, 2015; Hardimon, 2017) whereas Risch et al (2002) and Tang et al (2002) concur that race is useful in the biomedical sciences. (See also Dorothy Roberts’ Ted Talk The problem with race-based medicine which I will cover in the future). Richard Lewontin, naturally, has hang-ups here but his contentions are taken care of above. Even if race were a ‘social construct‘, as Lewontin says, it would still be useful in a biomedical sense; but since there are differences between races/ethnic groups then they most definitely are useful in a biomedical sense, even if at the end of the day individual variation matters more than racial variation. Just knowing someone’s race and SES, for instance, can tell you a lot about possible maladies they may have, even if, utltimately, individual differences in physiology and anatomy matter more in regards to the biomedical context.
In conclusion, race is most definitely a useful concept in medicine, whether race is a ‘social construct’ or not. Just using Michael Hardimon’s race concepts, for instance, shows that race is extremely useful in the biomedical context, despite what naysayers may say. Yes, individual differences in anatomy and physiology trump racial differences, but just knowing a few things like race and SES can tell a lot about a particular person, for instance with blood pressure, resting metabolic rate, and so on. Denying that race is a useful concept in the biomedical sciences will lead to more—not less—racial health disparities, which is ironic because that’s exactly what race-deniers do not want. They will have to accept a race concept, and they would accept Hardimon’s socialrace concept because that still allows it to be a ‘social construct’ while acknowledging that race and psychosocial factors interact to cause higher physiological variables. Race is a useful concept in medicine, and if the medical establishment wants to save more lives and actually end the racial disparities in health then they should acknowledge the reality of race.
Black-white differences in physiology can tell a lot about how the two groups have evolved over time. On traits like resting metabolic rate (RMR), basal metabolic rate (BMR), adiposity, heart rate, Vo2 max, etc. These differences in physiological variables between groups, then, explain part of the reason why there are different outcomes in terms of life quality/mortality between the two groups.
Right away, by looking at the average black and average white, you can see that there are differences in somatype. So if there are differences in somatype, then there must be differences in physiological variables, and so, this may be a part of the cause of, say, differing obesity rates between black and white women (Albu et al, 1997) and even PCOS (Wang and Alvero, 2013).
Resting metabolic rate
Resting metabolic rate is your body’s metabolism at rest, and is the largest component of the daily energy budget in modern human societies (Speakman and Selman, 2003). So if two groups, on average, differ in RMR, then one with the lower RMR may have a higher risk of obesity than the group with the higher RMR. And this is what we see.
Black women do, without a shadow of a doubt, have a lower BMR, lower PAEE (physical activity energy expenditure) and TDEE (total daily expenditure) (Gannon, DiPietro, and Poehlman, 2000). Knowing this, then it is not surprising to learn that black women are also the most obese demographic in the United States. This could partly explain why black women have such a hard time losing weight. Metabolic differences between ethnic groups in America—despite living in similar environments—show that a genetic component is responsible for this.
There are even predictors of obesity in post-menopausal black and white women (Nicklas et al, 1999). They controlled for age, body weight and body composition (variables that would influence the results—no one tell me that “They shouldn’t have controlled for those because it’s a racial confound!”) and found that despite having a similar waist-to-hip ratio (WHR) and subcutaneous fat area, black women had lower visceral fat than white women, while fasting glucose, insulin levels, and resting blood pressure did not differ between the groups. White women also had a higher Vo2 max, which remained when lean mass was controlled for. White women could also oxidize fat at a higher rate than black women (15.4 g/day, which is 17% higher than black women). When this is expressed as percent of total kcal burned in a resting state, white women burned more fat than black women (50% vs 43%). I will cover the cause for this later in the article (one physiologic variable is a large cause of these differences).
We even see this in black American men with more African ancestry—they’re less likely to be obese (Klimentidis et al 2016). This, too, goes back to metabolic rate. Black American men have lower levels of body fat than white men (Vickery et al, 1988; Wagner and Heyward, 2000). All in all, there are specific genetic variants and physiologic effects, which cause West African men to have lower central (abdominal) adiposity than European men and black women who live in the same environment as black men—implying that genetic and physiologic differences between the sexes are the cause for this disparity. Whatever the case may be, it’s interesting and more studies need to be taken out so we can see how whatever gene variants are *identified* as protecting against central adiposity work in concert with the system to produce the protective effect. Black American men have lower body fat, therefore they would have, in theory, a higher metabolic rate and be less likely to be obese—while black women have the reverse compared to white women—a lower metabolic rate.
Skeletal muscle fiber
Skeletal muscle fibers are the how and why of black domination in explosive sports. This is something I’ve covered in depth. Type II fibers contract faster than type I. This has important implications for certain diseases that black men are more susceptible to. Though the continuous contraction of the fibers during physical activity leads to a higher disease susceptibility in black men—but not white men (Tanner et al, 2001). If you’re aware of fiber type differences between the races (Ama et al, 1986; Entine, 2000; Caeser and Henry, 2015); though see Kerr (2010’s) article The Myth of Racial Superiority in Sports for another view. That will be covered here in the future.
Nevertheless, fiber typing explains racial differences in sports, with somatype being another important variable in explaining racial disparities in sports. Two main variables that work in concert are the somatype (pretty much body measurements, length) and the fiber type. This explains why blacks dominate baseball and football; this explains why ‘white men can’t jump and black men can’t swim’. Physiological variables—not only ‘motivation’ or whatever else people who deny these innate differences say—largely explain why there are huge disparities in these sports. Physiology is important to our understanding of how and why certain groups dominate certain sports.
This is further compounded by differing African ethnies excelling in different running sports depending on where their ancestors evolved. Kenyans have an abundance of type I fibers whereas West Africans have an abundance of type II fibers. (Genetically speaking, ‘Jamaicans’ don’t exist; genetic testing shows them to come from a few different West African countries.) Lower body symmetry—knees and ankles—show that they’re more symmetrical than age-matched controls (Trivers et al, 2014). This also goes to show that you can’t teach speed (Lombardo and Deander, 2014). Though, of course, training and the will to want to do your best matter as well—you just cannot excel in these competitions without first and foremost having the right physiologic and genetic make-up.
Further, although it’s only one gene variant, ACTN3 and ACE explain a substantial percentage of sprint time variance, which could be the difference between breaking a world record and making a final (Papadimitriou et al, 2016). So, clearly, certain genetic variants matter more than others—and the two best studied are ACTN3 and ACE. Some authors, though, may deny the contribution of ACTN3 to elite athletic performance—like one researcher who has written numerous papers on ACTN3, Daniel MacArthur. However, elite sprinters are more likely to carry the RR ACTN3 genotype compared to the XX ACTN3 genotype, and the RR ACTN3 genotype—when combined with type II fibers and morphology—lead to increased athletic performance (Broos et al, 2016). It’s also worth noting that 2 percent of Jamaicans carry the XX ACTN3 genotype (Scott et al, 2010), so this is another well-studied variable that lends to superior running performance in Jamaicans.
In regards to Kenyans, of course when you are talking about genetic reasons for performance, some people don’t like it. Some may say that certain countries dominate in X, and that for instance, North Africa is starting to churn out elite athletes, should we begin looking for genetic advantages that they possess (Hamilton, 2000)? Though people like Hamilton are a minority view in this field, I have read a few papers that there is no evidence that Kenyans possess a pulmonary system that infers a physiologic advantage over whites (Larsen and Sheel, 2015).
People like these three authors, however, are in the minority here and there is a robust amount of research that attests to East African running dominance being genetic/physiologic in nature—though you can’t discredit SES and other motivating variables (Tucker, Onywera, and Santos-Concejero, 2015). Of course, a complex interaction between SES, genes, and environment are the cause of the success of the Kalenjin people of Kenya, because they live and train in such high altitudes (Larsen, 2003), though the venerable Bengt Saltin states that the higher Vo2 max in Kenyan boys is due to higher physical activity during childhood (Saltin et al, 1995).
The last variable I will focus on (I will cover more in the future) is blood pressure. It’s well known that blacks have higher blood pressure than whites—with black women having a higher BP than all groups—which then leads to other health implications. Some reasons for the cause are high sodium intake in blacks (Jones and Hall, 2006); salt (Lackland, 2014; blacks had a similar sensitivity than whites, but had a higher blood pressure increase); while race and ethnicity was a single independent predictor of hypertension (Holmes et al, 2013). Put simply, when it comes to BP, ethnicity matters (Lane and Lip, 2001).
While genetic factors are important in showing how and why certain ethnies have higher BP than others, social factors are arguably more important (Williams, 1992). He cites stress, socioecologic stress, social support, coping patterns, health behavior, sodium, calcium, and potassium consumption, alcohol consumption, and obesity. SES factors, of course, lead to higher rates of obesity (Sobal and Stunkard, 1989; Franklin et al, 2015). So, of course, environmental/social factors have an effect on BP—no matter if the discrimination or whatnot is imagined by the one who is supposedly discriminated against, this still causes physiologic changes in the body which then lead to higher rates of BP in certain populations.
Poverty does affect a whole slew of variables, but what I’m worried about here is its effect on blood pressure. People who are in poverty can only afford certain foods, which would then cause certain physiologic variables to increase, exacerbating the problem (Gupta, de Wit, and McKeown, 2007). Whereas diets high in protein predicted lower BP in adults (Beundia et al, 2015). So this is good evidence that the diets of blacks in America do increase BP, since they eat high amounts of salt, low protein and high carb diets.
Still, others argue that differences in BP between blacks and whites may not be explained by ancestry, but by differences in education, rather than genetic factors (Non, Gravlee, and Mulligan, 2012). Their study suggests that educating black Americans on the dangers and preventative measures of high BP will reduce BP disparities between the races. This is in-line with Williams (1992) in that the social environment is the cause for the higher rates of BP. One hypothesis explored to explain why this effect with education was greater in blacks than whites was that BP-related factors, such as stress, poverty and racial discrimination (remember, even if no racial discrimination occurs, any so-called discrimination is in the eye of the beholder so that will contribute to a rise in physiologic variables) and maybe social isolation may be causes for this phenomenon. Future studies also must show how higher education causes lower BP, or if it only serves as other markers for the social environment. Nevertheless, this is an important study in our understanding of how and why the races differ in BP and it will go far to increase our understanding of this malady.
This is not an exhaustive list—I could continue writing about other variables—but these three are some of the most important as they are a cause for higher mortality rates in America. Understanding the hows and whys of these variables will have us better equipped to help those who suffer from diseases brought on by these differences in physiological factors.
The cause for some of these physiologic differences come down to evolution, but still others may come down to the immediate obesogenic environment (Lake and Townshend, 2006) which is compounded by lower SES. Since high carbs diets increase BP, this explains part of the reason why blacks have higher BP, along with social and genetic factors. Muscle fiber typing is set by the second trimester, and no change is seen after age 6 (Bell, 1980). Resting metabolic rate gap differences between black and white women can be closed, but not completely, if black women were to engage in exercise that use their higher amounts of type II muscle fibers (Tanner et al, 2001). This research is important to understand differences in racial mortality; because when we understand them then we can begin to theorize on how and why we see these disparities.
Physiologic differences between the races are interesting, they’re easily measurable and they explain both disparities in sports and mortality by different diseases. Once we study these variables more, we will be better able to help people with these variables—race be dammed. Race is a predictor here, only because race is correlated with other variables that lead to negative health outcomes. So once we understand how and why these differences occur, then we can help others with similar problems—no matter their race.
Last month I argued that there was more to weight loss than CI/CO. One of the culprits is a virus called Ad-36. Obese people are more likely to have Ad-36 antibodies in comparison to lean people, which implies that they have/had the virus and could be a part of the underlying cause of obesity. However, a paper was recently published that your stool can predict whether or not you can lose weight. This is due to how certain bacteria in the gut respond to different macronutrients ingested into the body.
ScienceDaily published an article a few days ago titled Your stools reveal whether you can lose weight. In the article, they describe the diets of the cohort, which followed 31 people, some followed the New Nordic Diet (NND), while others followed the Average Danish Diet (ADD) (Hjorth et al, 2017; I can’t find this study!! I’ll definitely edit this article after I read the full paper when it is available). So 31 people ate the NDD for 26 weeks, and lost 3.5 kg (7.72 pounds for those of us who use freedom numbers) while those who ate the ADD lost an average of 1.7 kg (3.75 pounds for those of us who use freedom numbers). So there was a 1.8 kg difference in pounds lost between the two diets. Why?
Here’s the thing: when people were divided by their microbiota, those who had a higher proportion of Prevotella to Bacteriodoites lost 3.5 more kg (7.72 pounds) in 26 weeks when they ate the NND in comparison to the ADD. Those who had a lower proportion of Prevotella to Bacteriodoites lost no additional weight on the NND. Overall, they say, about 50 percent of the population would benefit from the NND, while the rest of the population should diet and exercise until new measures are found.
The New Danish Diet is composed of grains, fruits, and vegetables. The diet worked for one-half of the population, but not for the other. The researchers state that people should try other diets and to exercise for weight loss while they study other measures. This is important to note: the same diet did not induce weight loss in a population; the culprit here is the individual microbiome.
Now that those Bacteroidotes have come up again, this quote from Allana Collen’s 2014 book 10% Human: How Your Body’s Microbes Hold the Key to Health and Happiness:
But before we get too excited about the potential for a cure for obesity, we need to know how it all works. What are these microbes doing that make us fat? Just as before, the microbiotas in Turnbaugh’s obese mice contained more Firmicutes and fewer Bacteroidetes, and they somehow seemed to enable the mice to extract more energy from their food. This detail undermines one of the core tenets of the obesity equation. Counting ‘calories-in’ is not as simple as keeping track of what a person eats. More accurately, it is the energy content of what a person absorbs. Turnbaugh calculated that the mice with the obese microbiota were collecting 2 per cent more calories from their food. For every 100 calories the lean mice extracted, the obese mice squeezed out 102.
Not much, perhaps, but over the course of a year or more, it adds up. Let’s take a woman of average height. 5 foot 4 inches, who weights 62 kg (9st 11 lb) and a healthy Body Mass Index (BMI: weight (kg) /(height (m)^2) of 23.5. She consumes 2000 calories per day, but with an ‘obese’ microbiota, her extra 2 per cent calorie extraction adds 40 more calories each day. Without expending extra energy, those further 40 calories per day should translate, in theory at least, to a 1.9 kg weight gain over a year. In ten years, that’s 19 kg, taking her weight to 81 kg (12 st 11 lb) and her BMI to an obese 30.7. All because of just 2 percent extra calories extracted from her food by her gut bacteria.
This corresponds with the NND/ADD study on weight loss… This proves that there is more than the simplistic CI/CO to weight loss, and that an individual’s microbiome/physiology definitely does matter in regards to weight loss. Clearly, to understand the population-wide problem of obesity we must understand the intricate relationship between the microbiome/brain/gut/body relationship and how it interacts with what we eat. Because evidence is mounting that the individual’s microbiome houses the key to weight loss/gain.
Exercise does not induce weight loss. A brand new RCT (randomized controlled trial) showed that in a cohort of children who were made to do HIIT (high-intensity interval training) did show better cardiorespiratory fitness, but there were no concomitant reductions in adiposity and bio blood markers (Dias et al, 2017). What this tells me is that people should exercise for health and that ‘high’ that comes along with it; if people exercise for weight loss they will be highly disappointed. Note, I am NOT saying to not exericse, I’m only saying to not have any unrealistic expectations that cardio will induce it, it won’t!
Bjornara et al (2016) showed that, when the NND was compared to the ADD, there was better adherence to the NND when compared to the ADD. Poulskin et al (2015) showed that the NND provided higher satisfaction, and body weight reduction with higher compliance with the NND and with physical activity (I disagree there, see above).
This study is important for our understanding of weight loss for the population as a whole. More recent evidence has shown that our microbiome and body clock work together to ‘pack on the pounds‘. This recent study found that the microbiome “regulate[s] lipid (fat) uptake and storage by hacking into and changing the function of the circadian clocks in the cells that line the gut.” The individual microbiome could induce weight gain, especially when they consume a Western diet, which of course is full of fat and sugar. One of the most important things they noticed is that mice without a microbiome fared much better on a high-fat diet.
The microbiome ‘talks’ to the gut lining. Germ-free mice were genetically unable to make NFIL3 in the cell lining of the gut. So germ-free mice lack a microbiome and lower than average production of NFIL3, meaning they take up and store fewer lipids than those with a microbiome.
So the main point about this study is the circadian rhythm. The body’s circadian clock recognizes the day/night system, which of course are linked to feeding times, which turn the body’s metabolism on and off. Cells are not directly exposed to light, but they capture light cues from visual and nervous systems, which then regulates gene expression. The gut’s circadian clock then regulates the expression of NFIL3 and the lipid metabolic machinery which is controlled NFIL3. So this study shows how the microbiome interacts with and impacts metabolism. This could also, as the authors state, explain how and why people who work nights and have shift-work disorder and the concurrent metabolic syndromes that come along with it.
In regards to the microbiome and weight loss, it is poorly understood at the moment (Conlon and Bird, 2015), though a recent systematic review showed that restrictive diets and bariatric surgery “reduce microbial abundance and promote changes in microbial composition that could have long-term detrimental effects on the colon.” They further state that “prebiotics might restore a healthy microbiome and reduce body fat“(Segenfrado et al, 2017). Wolf and Lorenz (2012) show that using “good” probiotic bacteria may induce changes in the obese phenotype. Bik (2015) states that learning more about the microbiome, dysbiosis (Carding et al, 2015), and how the microbiome interacts with our metabolism, brain, and physiology, then we can better treat those with obesity due to the dysbiosis of the microbiome. Clark et al (2012) show how the mechanisms behind the microbiota and obesity.
Weight loss is, clearly, more than CI/CO, and once we understand other mechanisms of weight loss/gain/regulation then we can better treat people with these metabolic syndromes that weirdly are all linked to each other. Diets affect the diversity of the microbiome, the diversity of the microbiome already there though, may need other macro/micro splits in order to show differing weight loss, in the case of the NND and ADD study reviewed above. Changes in weight do change the diversity of the microbiome of an individual, however, the heritable component of the microbiome may mean that some people need to eat different foods compared to others who have a different microbiome. Over time, new studies will show how and why the macro/micronutrient content matters for weight loss/gain.
Clearly, reducing the complex physiological process of weight gain/loss to numbers and ignoring the physiological process and how the microbiome induces weight gain/loss and works together with our other body’s cells. As the science grows here we will have a much greater understanding of our body’s weight loss mechanisms. Once we do that, then we can better help people with this disease.
The debate on human potential—and whether or not it is innate and ‘in the genes’—is steeped in bias and ideology from both sides (despite the claims that HBD ‘has no ideological bias’). Hereditarians assume that human potential is ‘in the genes’, and some even believe that human potential is testable during embryonic development (like psychologist Stuart Ritchie). However, this assumes two things: 1) that genes are the masters of development, and not the slaves, and 2) that differences in potential are already encoded in the genes of the homunculus. I will show that these two assumptions are wrong.
Embryonic development is a part of a larger whole of a complex process. Cells, in the beginning of embryonic development, are totipotent—meaning they have the ability to become any type of cell (Condic, 2014) depending on what the intelligent system calls for. This is important to note: at the beginning, all cells are the same and, despite having the same genes, “they have the same potential to become any kind of differentiated cell for a particular organism” (Richardson, 2017: 156). It is also possible to grow stem cells in a lab that are pluripotent—which have the ability to become any cell in the body—called iPS cells.
Even embryos that are of low quality do end up developing into healthy babes (emphasis in second para mine):
Embryo quality as we see it under the microscope in the IVF lab gives us some reasonable ability to predict the chances for pregnancy after the embryo transfer procedure. However, because there are many other contributing factors involved that we can not see or measure, the generalizations about “quality” made from grading embryos are often inaccurate.
We see some cycles fail after transferring 3 perfect looking embryos, and we also see beautiful babies born after transferring only one “low grade” embryo. The true genetic potential of the embryo to continue normal development is very difficult to measure accurately unless we utilize preimplantation genetic screening (PGS) to select chromosomally normal embryos for transfer.
So it seems that not even just looking at the quality of the embryo will show you if it will grow into a healthy baby with no birth complications. Potential must come after the embryonic stage of development. Another thing about testing the ‘quality’ of the embryo: it tells nothing about “what is going on inside the embryo genetically“.
The thing is, most chromosomal and other defects in any embryos can be noted under a microscope within 3 days of the embryo forming. And if you paid attention to totipotent cells earlier, you’d know that those cells have the potential to become any cell in the body—which is driven by the body’s intelligent systems/cells.
So embryonic quality really has no bearing on whether or not the embryo will eventually reach birth. As I’ve argued before in Human Mating and Aggression—An Evolutionary Perspective, the age of the mother is one of the strongest predictors of whether or not there will be deleterious effects on the child—mostly after 35 years of age (O’Reilly-Green and Cohen, 1993; van Katwijk and Peeters, 1998; Stein and Susser, 2010; Lampinen, Vehviläinen-Julkunen, and Kankkunen, 2009, Jolly, 2010; Yaniv et al, 2010; Liu et al, 2011). However, there is evidence that a woman can be too young to become a mother (Geronimus, Korenman, and Hillemeier, 1994; Fall et al, 2015) and that children born to young mothers “might be better off if the parents waited a few years” (Myrskyla and Fenelon, 2012). The same holds true for fathers, with it recently being observed that older fathers and their offspring have lower evolutionary fitness even over across four centuries (Arslan et al, 2017). So it seems that the best predictor of embryonic quality is parental age (Scheffer et al, 2017)—not what an embryo really looks like or the totipotent cells already in the embryo.
So there is no test for the genetic potential of embryos and sperm—with the best tell being parental age. Embryonic development is a part of the intelligent developmental system and each stage of embryonic development is brand new, rather than being the cause of an already laid out blueprint. So even though the embryo has all of the same genes (in totipotent cells), they have the potential to become any cell in the body which is directed by the intelligent system (as noted above).
So if you understand embryonic development and how it’s a part of the intelligent system itself and not a part of an already laid out blueprint, then you’ll understand how potential—as we know it— is not in the embryo. They all have the same kinds of totipotent cells which have the chance to become any cell in the body which are then activated and used by the intelligent physiology. The age of both parents are the best predictors of embryonic quality—just by looking at the embryos after they’ve developed from blastocytes, you cannot infer that embryo’s potential.
Ken Richardson also responded to Stuart Ritchie’s article It’s now possible, in theory, to predict life success from a genetic test at birth to which Ken Richardson responded to. Potential is not in the embryo due to the number of totipotent cells in the embryo. Even ‘low-quality’ embryos can become healthy babes, so ’embryonic quality’ is not a good measure of whether or not it will be born with a defect, etc.
Another day, another slew of articles full of fear mongering. This one is on sperm decline in the West. Is it true? I have recently covered on this blog that as of July 17th, 2017, the testosterone range for men decreased (more on that when I get access to the paper). I have also covered the obesity epidemic a bit, and that also factors in to lowered testosterone and, of course, low spermatoza count. Due to these environmental factors, we can logically deduce that sperm counts have fallen as well. However, as I will cover, it may not be so cut and dry due to analyzing numerous studies with different counting methodologies among numerous other confounds that will be addressed below. First I will cover the physiology of sperm production and what may cause decreases in production. Next, I will cover the new study that is being passed around. Finally, I will talk about why you should worry about this.
Physiology of sperm production
The accumulation of testosterone by ABP leads to the onset and rising rate of sperm production. So if testosterone production ceases or decreases, then subsequent decreases in sperm count and spermatogenesis should follow. If this change is drastic, infertility will soon follow. The process of sperm production is called spermatogenesis. It occurs in the seminiforous tubules and involves three main events: 1) remodeling relatively large germ cells into smaller mobile cells with flagella, 2) reducing the chromosome number by half, and 3) shuffling the genes so that each chromosome in the sperm carries novel gene combinations that differ from the parents. This is what ensures that a child will differ from their parents but still, at the same time, will be similar to them. The process by which this occurs is called meiosis, in which four daughter cells split which subsequently differentiate sperm (Saladin, 2010: 1063).
After the conclusion of meiosis I, each chromosome is still double stranded, except each daughter cell only has 23 chromosomes becoming a haploid while at the end of meiosis II, there are four haploid cells with 23 single-stranded chromosomes. Fertilization then combined the 23 chromosomes from the father and mother, which “reestablishes the diploid number of 46 chromosomes in the zygote“(Saladin, 2010: 1063-1064).
Spermatogonia divide by mitosis and then enlarge to become primary spermatocyte. The cell is then protected from the immune system since it is going to become genetically different from the rest of the cells in the body. Since the cells are guarded from the body’s immune system, the main spermatocyte undergoes meiosis I, giving rise to equal size haploid and genetically unique secondary spermatocytes. Then, each secondary spermatocyte undergoes meiosis II dividing into two spermatids with a total of four spermatogoniom. Lastly, the spermatozoa undergo no further division but undergoes spermiogenesis in which it differentiates into a single spermatozoon (Saladin, 2010: 1065-1066). Young men produce about 300,000 sperm per minute, about 400 million per day.
The new study was published on July 25, 2017, in the journal Human Reproduction Update titled Temporal trends in sperm count: a systematic review and meta-regression analysis. Levine et al (2017) used 185 studies (n=42,935) and showed a sperm count (SC) decline of .75 percent per year, coming out to a 28.5 percent decrease between 1975 and 2011. Similar declines were seen in total sperm count (TSC) while 156 estimates of serum volume showed little change.
Figure 2a shows the mean sperm concentration between the years 1973 and 2011. Figure 2b shows the mean total sperm count between those same years.
Figure 3a shows sperm concentration for the West (North America, Australia, Europe and New Zealand) vs Other (South America, Asia, and Africa), adjusted for potential confounders such as BMI, smoking etc. Figure 3b shows total sperm count by fertility and the West and Other. You can see that Fertile Other had a sharp increase, but the increase may be due to limited statistical power and a lack of studies of unselected men from those countries before 1985. There is a sharp increase for Other, however and so the data does not support as sharp of a decline as observed in Western countries.
If this is true, why is this happening? Factors that decrease spermatogenesis include (but are not limited to): obesity, smoking, exposure to traffic exhaust fumes, and combustion products. Though there is no data (except animal models) that lend credence to the idea that pesticides, food additives, etc decrease spermatogenesis (Sharpe, 2010). Other factors are known to cause lower SC which includes maternal smoking, alcohol, stress, endocrine disruptors, persistent and nonpersistent chemicals, and, perhaps most importantly today, the use of mobile phones and the wireless Internet (Virtanen, Jorgansen, and Toparri, 2017). Radiation exposure due to constant mobile phone use may cause DNA fragmentation and decreased sperm mobility (Gorpinchenko et al, 2014). Clearly, most of this decrease can largely be ameliorated. Exercise, eating right, and not smoking seem to be the most immediate changes that can and will contribute to an increase in SC in Western men. This will also increase testosterone levels. The cause is largely immobility due to the comfortable lifestyles that we in the West have. So by becoming more active and putting down smartphones, we can then begin to reverse this downward trend.
Saladin (2010: 1067) also states that pollution has deleterious effects on reproduction—and by proxy, sperm production. He states that the evidence is mounting that we are showing declining fertility due to “anatomical abnormalities” in water, meat, vegetables, breast milk and the uterus. He brings up that sperm production decreased in 15,000 men in 1990, decreasing from 113 million/ml in 1940 to 66 million/ml in 1990. Sperm production decreased more, he says, since “the average volume of semen per ejaculate has dropped 19% over this period” (Saladin, 2010: 1067).
Saladin (2010: 1067) further writes:
The pollutants implicated in this trend include a wide array of common herbicides, inseciticides, industrial chemicals, and breakdown products of materials ranging from plastics to dishwashing detergents. Some authorities think these chemicals act by mimicking estrogens by blocking the action of testosterone by binding to its receptors. Other scientists, however, question the data and feel the issue may be overstated. While the debate continues, the U.S. Environmental Protection Agency is screening thousands of industrial chemicals for endocrine effects.
Is it really true?
As seen above, the EPA is investigating whether thousands of industrial chemicals of effects on our endocrine system. If this is true, it occurs due to the binding of these chemicals to androgen receptors, blocking the production of testosterone and thusly sperm production. However, some commentators have contested the results of studies that purport to show a decrease in SC in men over the decades.
Sherins and Delbes are critical of such studies. They rightly state that most of these studies have numerous confounds such as:
1) lack of standardized counting measures, 2) bias introduced by using different counting methodologies, 3) inadequate within-individual semen sampling in the analysis, 4) failure to account for variable abstinence intervals and ejaculatory frequency, 5) failure to assess total sperm output rather than concentration, 6) failure to assess semen parameteres other than the number of sperm, 7) failure to account for age of subject, 8) subject selection bias among comparitive studies, 9) inappropriate statistical analysis, 10) ignoring major geographic differences in sperm counts, and 11) the causal equating of male ferility with sperm count per se.
Levine et al (2017) write:
We controlled for a pre-determined set of potential confounders: fertility group, geographic group, age, abstinence time, whether semen collection and counting methods were reported, number of samples per man and indicators for exclusion criteria (Supplementary Table S1).
So they covered points 1, 2, 4, 5, 6, 7, 8, 9, and 10. This study is very robust. Levine et al (2017) replicate numerous other studies showing that sperm count has decreased in Western men (Centola et al, 2015; Senputa et al, 2017; Virtanen, Jorgensen, and Toparri, 2017). Men Southern Spain show normal levels (Fernandez et al, 2010), while Southern Spanish University students showed a decrease (Mendiola et al, 2013). The same SC decrease has been noted in Brazil in the last ten years (Borges Jr. et al, 2015).
However, te Velde and Bonde (2013) in their paper Misconceptions about falling sperm counts and fertility in Europe contest the results of studies that argue that SC has decreased within the last 50 years stating that, for instance in Denmark, the median values remained between 40-45 million sperm per ml in the 15 years analyzed. They also state that declining birth rates can be explained by cultural and social factors, such as contraception, the female emancipation, and the second demographic transition. Clearly, ferility rates are correlated with the human development index (HDI) meaning that more developed countries have a lower birth rate in comparison to less developed countries. I believe that part of the reason why we in the West have lower birth rates is because there are too many things to for us to do to occupy our time, time that could be used to have children, like going to school to pursue Masters degrees and PhDs, to just wanting more ‘me time’.
Te Velde and Bonde (2013) conclude:
‘Whether the sperm concentration and human fecundity have declined during the past 50 years is a question we will probably never be able to answer’. This statement by Olsen and Rachootin in 200348 still holds for sperm concentration despite the report in 1992. In the meantime, we know that the results of oft-repeated studies from Copenhagen and Malmö do not indicate any notable change in sperm count during the last 10–15 years. Moreover, none of the available evidence points to a decline in couple fecundity during the last 30–40 years, including Denmark.28 Moreover, birth rates and TFRs instead of declining are on the increase in many EU countries, including the spectacular rise in Denmark.34
Echoing the same sentiments, Cocuzza and Esteves (2014) conclude “that there is no enough evidence to confirm a worldwide decline in sperm counts or other semen parameters. Also, there is no scientific truth of a causative role for endocrine disruptors in the temporal decline of sperm production as observed in some studies. We conjecture that a definite conclusion would only be achieved if good quality collaborative long-term research was carried out, including aspects such as semen quality, reproductive hormones, and xenobiotics, as well as a strict definition of fecundity.” Merzenich, Zeeb, and Blettner (2010) also caution that “The observed time trend in semen quality might be an artefact, since the methodological differences between studies might be time dependent as well. Intensive research will be necessary in both clinical and epidemiological domains. More studies are needed with strict methodological standards that investigate semen quality obtained from large samples of healthy men representative for the normal male population.”
Clearly, this debate is long and ongoing, and I doubt that even Levine et al (2017) will be good enough for some researchers.
There are various papers for and against a decrease in sperm production in the West, just like with testosterone. However, there are ways we can deduce that SC has fallen in the West, since we have definitive data that testosterone levels have decreased. This, then, would lead to a decrease in sperm production and then fecundity and number of children conceived by couples. Of course, sociocultural factors are involved, as well as immediate environmental ones that are immediately changeable. Even if there is no scientific consensus on industrial chemicals and effects on the endocrine system, you should stay away from those too. One major reason for the decrease in sperm production—if the decrease is true—is increased mobile phone usage. Mobile phone usage has increased and so this would lower SC over time.
Whether or not the decrease in SC is true or not, every man should take steps to lead a healthier lifestyle without their cell phone. Because if this decrease is true (and Other doesn’t show a decrease as well) then it would be due to the effects of our First World societies, which would mean that we need to change how we live our lives to get back on the right track. Clearly, we must change our diets and our lifestyles. I’ve written numerous articles about how testosterone is strongly mediated by the environment, and that testosterone production in men has decreased since Western men have been, in a way, feminized and not been as dominant. This can and does decrease testosterone production which would, in turn, decrease sperm production and decrease fertility rates.
Nevertheless, taking steps to leading a healthier lifestyle will ameliorate a ton of the problems that we have in the West, which are mainly due to low birth rates, and by ameliorating these problems, the quality of life will the increase in the West. I am skeptical of the decrease due to what was brought up above, but nevertheless I assume that it is true and I hope my readers do too—if only to get some fire under you to lead a healthier lifestyle if you do not do so already as to prevent these problems before they occur and lead to serious deleterious health consequences.
(I am undecided leaning towards yes. There are too many behaviors linked to lower SC which Western men partake in. There are numerous confounds which may have not been controlled for, however knowing the main reasons why men have lower sperm count and the increased prevalence in these behaviors, we can logically deduce that sperm count has fallen too. Look to the testosterone decrease, that causes both low sperm count and lower fertility.)
When organisms that we don’t normally signify as ‘intelligent’ do, indeed, show ‘intelligent’ behavior, our definition of the word—what we call ‘intelligent’ behavior—needs to be reevaluated. Bacteria and other microbes can certainly respond to cues from their environments and communicate with each other. So if bacteria can respond to environmental stimulus by having plastic behavior, then they do show a semblance of ‘intelligence’. Just because bacteria don’t talk doesn’t mean that they are not ‘intelligent’ in their own right.
Bacteria respond to cues from their environment, just like any other intelligent organism. That means that they have behavioral plasticity, the ability to change their behavior based on what occurs in their environments. Bacteria have been shown to exhibit behaviors we would call ‘intelligent’, i.e., acquiring information, storage, processing, use of information, perception, learning, memory, and decision-making (Lyon, 2015). It is proposed that “bacteria use their intracellular flexibility, involving signal transduction networks and genomic plasticity, to collectively maintain linguistic communication: self and shared interpretations of chemical cues, exchange of chemical messages (semantic) and dialogues (pragmatic)” (Jacob et al, 2004).
Clearly, bacteria can and do adapt at the phenotypic level, not only the genotypic level as some have asserted in the past. Using this definition of intelligence, that is, being able to perceive, process and integrate information about the state of the environment to change the organism’s behavior is intelligent behavior (Pinto and Mascher, 2016), all organisms, from bacteria to humans and in between are intelligent. If bacteria do show evidence of behavioral plasticity—and they do—then we must look at them as intelligent creatures, as well as come to the realization that all biological organisms are, in their own right, intelligent. Intelligence is not only for any ‘higher’ organisms; so-called ‘lower’ organisms do show behavioral plasticity, meaning they know what is occurring in their environment. Is that not intelligent?
Any organism that can immediately act in a different way when its environment changes can, in my opinion, be said to be intelligent. All biological organisms have this ability to ‘go off of their genetic coding’, if you will, and change their behavior to match what is currently going on in their environment. Furthermore, the number and fraction of single transduction genes can be used as a measure of ‘bacterial IQ’ (Sirota-Mahdi et al, 2010).
This, of course, has implications for our intelligent physiology. Since our physiological systems incorporate the intelligent processes of the intelligent cell, then, on a larger scale, our physiology is also intelligent. Our physiology is constantly responding to cues from the environment, attempting to maintain homeostasis. Since our body has a need to stay in homeostasis, then our physiological systems are indeed intelligent in their own right. They incorporate the processes of the intelligent cell; looking at our physiology in this way, we can see how and why these systems are intelligent.
Further, physiologists have been referring to physiological systems as “homeodynamic”, rather than “homeostatic”, seeing chaotic states as healthy “allowing organisms to respond to circumstances that vary rapidly and unpredictably, again balancing variation and optimization of order with impressive harmony” (Richardson, 2012). If our physiological systems can do this, are they not intelligent? Further, according to physiologist Dennis Noble, “Genes … are purely passive. DNA on its own does absolutely nothing until activated by the rest of the system through transcription factors, markers of one kind or another, interactions with the proteins. So on its own, DNA is not a cause in an active sense. I think it is better described as a passive data base which is used by the organism to enable it to make the proteins that it requires.” So, as you can see, genes are nothing without the intelligent physiology guiding then. This is only possible with physiological systems, and this begins with the intelligent cell—intelligent microbes.
Some people misunderstand what genes are for and what they do in the body. The gene has long been misunderstood. People don’t understand that genes direct the production of proteins. Since physiological systems—at their core—are run by microbes, then the overall physiological system is itself intelligent. Genes, on their own, are not the masters but the servants. Genes do code for proteins that code for traits, but not under their own direction; they are directed by intelligent systems.
Think of how our gut microbiome co-evolved with us. Knowing what we now know about intelligent cells, we can also say that, by proxy, our microbiome is intelligent as well.
Understanding intelligent cells will lead us to understand intelligent physiology then, in turn, lead us to understand how genes are the servants—not the masters as is commonly asserted—of our traits. Physiology is an intelligent system, and since it is intelligent it can then react to cues from the environment, since it is made up of smaller cells, which make up the larger whole of the intelligent physiological system. These intelligent systems that we have evolved are due to the changeability of our environments in our ancestral past. Our physiology then evolved to be homeodynamic, attempting to maintain certain processes. The ever-changing environment that our genus evolved in is the cause for our homeodynamic intelligent physiology, which begins at the smallest levels of the cell.
The intelligent microbes are the smaller part of the larger whole of the intelligent physiological system. Due to this, we can say that at the smallest levels, we are driven by infinitesimally small microbes, which, in a way, guide our behavior. This can definitely be said for our gut microbiome which evolved with us throughout our evolutionary history. Our microbiome, for instance, had to be intelligent and communicate with each other to maintain our normal functioning. Without these intelligent cells, intelligent physiology would not be possible. Without ever-changing dynamic environments, our intelligent physiology and intelligent cells would have never evolved.
Intelligent physiology evolved due to the constant changeability of the new environments that our ancestors found themselves in. If we would have evolved in, say, more stable, unchanging environments, our physiological systems would have never evolved how they did. These intelligent physiological systems can buffer large ranges of physiological deficiencies. The evolvability of these systems due to the changeability of our ancestral environments is the cause of our amazing physiological intelligence, developmental plasticity, and microbial intelligence.
When you think about conception, when a baby is forming in the womb, it becomes easier to see how our physiological systems are intelligent, and how genes are the slaves—not masters—of our development. Intelligence is already in those little cells, it just needs an intelligent physiology for things to be set into motion. This all goes back to the intelligent cells which make up the larger part of intelligent physiology.
The general factor of intelligence (g) is said to be physiological. Jensen (1998: xii) states that “Students in all branches of the behavioral and social sciences, as well as students of human biology and evolution, need to grasp the essential psychometric meaning of g, its basis in genetics and brain physiology, and its broad social significance.” There are, furthermore, “a number of suggestive neurological correlates of g, but as yet these have not been integrated into a coherent neurophysiological theory of g” (Jensen, 1998: 257). I personally don’t care for correlations too much anymore, I’m interested in actual causes. Jensen (1998: 578) also states “Although correlated with g [size of the brain, metabolic rate, nerve conduction velocity, and latency and amplitude of evoked electrical potentials], these physiological variables have not yet provided an integrated explanatory theory.”
This seems suspiciously like Dreary’s (2001: 14) statement that there “is no such thing as a theory of human intelligence differences – not in the way that grown-up sciences like physics or chemistry have theories.” If g is physiological, then where is the explanatory theory? On that same matter, where is the explanatory theory for individual intelligence differences? That’s one thing that needs to be explained, in my opinion. I could muster something up off the top of my head, such as individual differences in glucose metabolism in the brain, comparing both high and low IQ people (Cochran et al, 2006; Jensen, 1998: 137), however, that is still not good enough.
In physiology there is sliding filament theory which explains the mechanism of muscle contraction (Cooke, 2004). Why is there no such theory of why individuals differ in intelligence and why have these “suggestive neurological correlates of g” not been formulated into a coherent neurophysiological theory? There are numerous theories in physiology, but a theory of g or why individuals differ in intelligence is not one of them.
It’s like Darwin only saying “Species change“, and that’s it; no theory of how or why. He’s just stating something obvious. Similarly, saying “Person A is smarter or has a higher IQ than person B” is just an observation; there is no theory of how or why for why individuals differ in intelligence. There are theories for group differences (garbage cold winter theory), but no individual differences in intelligence? Hmmm… Sure it’d be a ‘fact that species change over time’, but without a theory of how or why, how useful is that observation? Similarly, it is true that some people are more intelligent than others (score higher on IQ tests), yet there is no explanatory theory as to why? I believe this ties back to the physiological basis for g: are physiologists studying it, and if not, why?
Reaction time (RT) is one of the most talked about physiological correlates in regards to IQ. However, as a fitness professional, I know that exercise can increase reaction time, especially in those with intellectual disabilities (Yildirim et al, 2001). I am now rethinking the correlate between reaction time and IQ, since it can be trained in children, especially those with intellectual disabilities. Clearly, RT can be trained by exercise, participating in sports, and even by playing video games (Green, 2008). So since RT can be trained, I don’t think it’s a good physiological measure for g.
Individuals do differ in individual physiology, however, I have never heard of a physiologist attempting to rank individuals on different traits, nevermind attempting to say that a higher level of one variable is better than a lower variable, say blood pressure or metabolic rate. In fact, individuals with high blood pressure and metabolic rates would need immediate medical attention.
There are also wide variations in how immune systems act when faced with pathogens, bacteria and viruses. Though, “no one dreams of ranking individual differences on a general scale of immunocompetence” (Richardson, 2017: 166). So if g is physiological then why don’t other physiological traits get placed on a rank order, with physiologists praising certain physiological functions as “better”?
Richardson (2017: 166-167) writes:
In sum, no physiologist would suggest the following:
(a) that within the normal range of physiological differences, a higher level is better than any others (as is supposed in the construction of IQ tests);
(b) that there is a general index or “quotient” (a la IQ) that could meaningfully describe levels of physiological sufficiency or ability and individual differences in it;
(c) that “normal” variation is associated with genetic variation (except in rare deleterious conditions; and
(d) the genetic causation of such variation can be meaningfully separated from the environmental causes of the variation.
A preoccupation with ranking variations, assuming normal distributions, and estimating their heritabilities simply does not figure in the field of physiology in the way that it does in the field of human intelligence. This is in stark contrast with the intensity of the nature-nurture debate in the human cognitive domain. But perhaps ideology has not infiltrated the subject of physiology as much as it has that of human intelligence.
This is all true. I know of no physiologist who would suggest such a thing. So does it make sense to compare g with physiological variables—even when classic physiological variables do not have some kind of rank order? Heritabilities for BMR are between .4 and .8, which is in the same range as the heritability of IQ. Can you imagine any physiologist on earth suggesting a rank order for physiological traits such as BMR or stroke volume? I can’t, and if you knew anything about physiological variables then you wouldn’t either.
In sum, I believe that conflating g with physiology is erroneous; mostly because physiologists don’t rank physiological traits in the same ways that human intelligence researchers do. Our physiology is intelligent in and of itself, and this process begins in the cell—the intelligent cell. Our physiological systems are intelligent—in our bodies are dynamic systems that keenly respond to whatever is going on in the environment (think of how the body always attempts to maintain homeostasis). Physiology deals with the study of living organisms—more to the point, how the systems that run the organisms work.
Looking at physiological variables and attempting to detangle environmental and genetic effects is a daunting task—especially the way our physiological systems run (responding to cues from the environment, attempting to maintain homeostasis). So if general intelligence—g—had a true biological underpinning in the body, and if physiologists did study it, then they would not have a rank ordering for g like psychologists do; it’d just be another human trait to study.
So the answer to the question “Do physiologists study g?” is no, and if they did they would not have the variable on a rank order because physiologists don’t study traits in that manner—if a true biological underpinning for g exists. Physiology is an intelligent and dynamic system in and of itself, and the process begins in the intelligent cell, except it is on a larger scale, with numerous physiological variables working in concert, constantly attempting to stay in homeostasis.