“In the pages that follow we advance two propositions.
First, people cooperate not only for self-interested reasons but also because they are genuinely concerned about the well-being of others, try to uphold social norms, and value behaving ethically for its own sake. People punish those who exploit the cooperative behavior of others for the same reasons. Contributing to the success of a joint project for the benefit of one’s group, even at a personal cost, evokes feelings of satisfaction, pride, even elation. Failing to do so is often a source of shame or guilt.
Second, we came to have these “moral sentiments” because our ancestors lived in environments, both natural and socially constructed, in which groups of individuals who were predisposed to cooperate and uphold ethical norms tended to survive and expand relative to other groups, thereby allowing these prosocial motivations to proliferate. The first proposition concerns proximate motivations for prosocial behavior, the second addresses the distant evolutionary origins and ongoing perpetuation of these cooperative dispositions.”
Here’s my goodreads review of the book – I gave the book five stars on goodreads. In the post I have included some illustrative quotes below, but really you should read all of it if you find this sort of stuff interesting and you’re not mathematically illiterate (and as the authors note early on, they have given the way they present their ideas some thought: “We have presented technical material in verbal as well as mathematical form wherever possible, and avoided mathematical formulations entirely where that was possible without sacrificing clarity.” Even so, the book is somewhat dense and it takes some work to get through).
“In short, humans became the cooperative species that we are because cooperation was highly beneficial to the members of groups that practiced it, and we were able to construct social institutions that minimized the disadvantages of those with social preferences in competition with fellow group members, while heightening the group-level advantages associated with the high levels of cooperation that these social preferences allowed. These institutions proliferated because the groups that adopted them secured high levels of within-group cooperation, which in turn favored the groups’ survival as a biological and cultural entity in the face of environmental, military and other challenges.”
“The regulation of social interactions by group-level institutions plays no less a role than altruistic individual motives in understanding how this cooperative species came to be. Institutions affect the rewards and penalties associated with particular behaviors, often favoring the adoption of cooperative actions over others, so that even the self-regarding are often induced to act in the interest of the group. […] the individual motives and group-level institutions that account for cooperation among humans include not only the most elevated, including a concern for others, fair-mindedness, and democratic accountability of leaders, but also the most wicked, such as vengeance, racism, religious bigotry, and hostility toward outsiders.”
“Optimizing models are commonly used to describe behavior not because they mimic the cognitive processes of the actors, which they rarely do, but because they capture important influences on individual behavior in a succinct and analytically tractable way.”
“Culture is an evolutionary force in its own right, not simply an effect of the interaction of genes and natural environments. […] human preferences and beliefs are the product of a dynamic whereby genes affect cultural evolution and culture affects genetic evolution, the two being tightly intertwined in the evolution of our species. [I have of course talked about gene-culture coevolution before here on the blog and I don’t like to repeat myself, but this idea/notion really is unknown to many people who should know better, and so is perhaps worth repeating here even so – US] […] The idea of treating culture as a form of epigenetic transmission was pioneered by Cavalli-Sforza and Feldman (1973), Karl Popper (1979), and Richard Dawkins, who coined the term “meme” […] to represent an integral unit of information that could be transmitted phenotypically. There quickly followed several major contributions to a biological approach to culture, all based on the notion that culture, like genes, could evolve through replication (intergenerational transmission), mutation, and selection […] Richard Dawkins added a second fundamental mechanism of epigenetic information transmission in The Extended Phenotype (1982), noting that organisms can directly transmit environmental artifacts to the next generation […] Creating a fitness-relevant aspect of an environment and stably transmitting this environment across generations, known as niche construction, is a widespread form of epigenetic transmission […] niche construction gives rise to what might be called a gene-environment coevolutionary process, since a genetically induced environmental regularity becomes the basis for genetic selection, and genetic mutations that give rise to mutant niches will tend to survive if they are fitness enhancing for their constructors. […] Human cultures, along with the institutional structures they support, are instances of niche construction”.
“while genetic transmission of information plays a central role in our account, the genetics of non-pathological social behavior is for the most part unknown. […] No “gene for cooperation” has been discovered. Nor is it likely that one will ever be found, for the idea of a one-to-one mapping between genes and behavior is unlikely given what is now known about gene expression, and is implausible in light of the complexity and cultural variation of cooperative behaviors. […] an explanation of the evolution of human cooperation must hinge on the empirical evidence. The question is not “Which model works?” They all work, if mathematical coherence is the bar. The question we are asking is about something that actually happened in the human past. Thus we measure the empirical plausibility of alternative explanations against the conditions under which early humans lived during the Pleistocene, roughly 1.6 million years before the present, until the advent of agriculture beginning about 12,000 years ago, and especially the last 100 or so millennia of this period.”
“in small-scale societies punishment can be highly effective even when it takes the form of ridicule or gossip and it inflicts no material costs on its targets. […] People are sensitive to others’ evaluation of their moral worth or intentions and will cooperate in social dilemmas when the punishment for free-riding takes the form of criticism by peers rather than a reduction in material payoffs. […] People punish not only those who have hurt them, but also those who hurt others. […] even self-regarding individuals may engage in third-party punishment if they believe that this will induce other-regarding individuals to behave favorably toward them. […] recent experimental results are consistent with the view that the social preferences that become salient in a population depend critically on the manner in which a people’s institutions and livelihood frame social interactions and shape the process of social learning. An expected result, confirmed by a growing body of international comparative evidence, is substantial cross-cultural differences in the nature and extent of social preferences.”
“In experimental and natural settings, people often behave differently toward others, depending on the organizational, linguistic, ethnic, and religious groups to which they belong. People choose to associate with others who are similar to themselves in some salient respect […] Among the salient characteristics on which this choice operates are racial and ethnic identification, and religion […] Conversely, people often seek to avoid interactions with those who are different from themselves. […] Those who condition their behavior on the group membership of the other may do this because group membership is thought to provide information about the other’s likely behavior. Or group membership may matter because people would like to help or to interact with members of some groups more than others. In the first case the actor’s beliefs are involved. In the second case, group-sensitive preferences are at work. […] a series of experiments by Toshio Yamagishi and his associates […] show that experimental subjects’ allocations favor in-group members not because of altruistic sentiments toward those who are similar to themselves, but because they expected reciprocation from in-groupers and not from out-groupers. […] taking account of ethnic, racial and other characteristics of those with whom one interacts appears to be a quite common human trait. We seem quite attuned to noticing and treating as salient the ascriptive markers of group difference. For example, Americans of European and African origin are better at recognizing faces of their own ancestral group, and faces of their own group induce greater activation in the part of the brain associated with face recognition.” (my bold)
“The most parsimonious and compelling proximate explanation of behavior in the ultimatum game, public goods game, and other social dilemma experiments is that people think that cooperating is the right thing to do and enjoy doing it, and that they dislike unfair treatment and enjoy punishing those who violate norms of fairness. […] Recent studies of brain functioning provide some support for this hedonic view of cooperative behavior.“
“Differential group success […] plays a central role in the evolution of human behaviors and institutions, members of less successful groups copying the more successful or being eliminated by them. […] the speed of an evolutionary process is proportional to the differences on which it works […] reduction in within-group differences slows down the selection against altruistic individuals. Insider biases and individual preferences to interact with like individuals lead to large between-group differences in behavior and, to a lesser but not negligible extent, in genotypes too […] insider biases result in frequent between-group conflicts as well as high levels of positive assortment in interactions both within and between groups. […] All of these aspects of human social life enhance the force of between-group selection relative to within-group selection.” (my bold)
“The fact that helping behaviors are […] motivated by [a] wide range of proximate motives, from maternal love, to enlightened self-interest, to solidarity with one’s coethnics or conationals, is consistent with our view that in all likelihood each of the mechanisms […] has played a significant role in human evolution, the importance of each depending on the forms of cooperation under consideration and the ecological and social conditions under which ancestral humans interacted. […] what can be known or reasonably conjectured from genetic, archaeological and other data about [the] ancestral human conditions suggests that neither helping close family members nor reciprocal altruism provides an adequate account of the emergence of [our] cooperative species. […] multi-level selection models based on gene culture coevolution [however] contribute substantially to a convincing explanation.”
As mentioned, if you find this kind of stuff interesting you should strongly consider reading the book.
“Data from animal studies in one country are usually comparable with that of another, provided the animal species and strain are the same. This provides a consistent picture of the basic pharmacological and toxicological actions of a candidate drug in a living organism […] it has been obvious since animal testing began that there would be large differences in the way a drug might perform in man compared with animal species […]. Unfortunately, there is no experimental model yet designed that can not only consider human biochemistry and physiology, but also the effects of age, smoking, legal and illegal drug usage, gender, diet, environment, disease and finally genetic variation. Indeed, many clinical studies have revealed enormous differences in drug clearance and pharmacological effect even in age, sex and ethnically matched individuals. In effect, this means that the first year or so of a drug’s clinical life is a vast, but monitored experiment, involving hundreds of thousands of patients and there is no guarantee of success.”
“Most biotransformational polymorphisms that might potentially cause a problem clinically are due to an inability of those with defective enzymes to remove the drug from the system. Drug failure can occur if the agent is administered as a pro-drug and requires some metabolic conversion to an active metabolite. Drug accumulation can lead to unpleasant side effects and loss of patient tolerance for the agent. […] Overall, there are a large number of factors that can influence drug metabolism, either by increasing clearance to cause drug failure, or by preventing clearance to lead to toxicity. In the real world, it is often impossible to delineate the different conflicting factors which result in net changes in drug clearance which cause a drug to fall out of, or climb above, the therapeutic window. It may only be possible clinically in many cases to try to change what appears to be the major cause to bring about a resolution of the situation to restore curative and non-toxic drug levels.”
“Most population studies of human polymorphisms list the allelic frequency, that is, how many of an ethnic group contain the alleles in question. […] The actual haplotypes in the population, that is, which individuals express which combinations of alleles, are not the same as the population allelic frequency. […] If an SNP or a combination of SNPs is a fairly mild defect in the enzyme when it is homozygously expressed, then the heterozygotes will show little impairment and the polymorphism may be clinically irrelevant. With other SNPs, the enzyme produced may be completely non-functional. Homozygotes will be virtually unable to clear the drug and heterozygotes will show impairment also. There are also smaller populations of UMs, or ultra rapid metabolizers which may have a feature of their enzyme which either makes it super efficient or expressed in abnormally high amounts. […] Phenotyping will group patients in very broad EMs [extensive metabolizers], IMs [intermediate metabolizers] or PM [poor metabolizers] categories, but will be unable to distinguish between heterozygous and homozygous EMs. Although genotyping may be very helpful in dosage estimation in the initiation of therapy, there is no substitute for the normal process of therapeutic monitoring, which is effectively phenotyping the individual in the real world in terms of maximizing response and minimizing toxicity.”
“it is clear that there is a vast amount of genetic variation across humanity in terms of biotransformational capability and so the idea that in therapeutics, ‘one size fits all’ is not only outdated, but fabulously naïve. […] Unfortunately, detecting and responding successfully to human biotransformational polymorphisms has proved to be extremely problematic. In terms of polymorphism detection, this area is a classic illustration of how the exploration of the human genome with powerful molecular biological tools may unearth many apparently marked polymorphic defects that may not necessarily translate into a measurable clinical impact in terms of efficacy and toxicity. In reality, many more scientists have the opportunity to discover and publish such polymorphisms in vitro, than there are clinical scientists, resources and indeed cooperative volunteers or patients in sufficient quantity to determine practical clinical relevance.”
“the CYP3A group (chromosome 7) metabolize around half of all drugs […] variation in the metabolism of CYP3A substrates […] can be up to ten-fold in terms of drug clearances and up to 90-fold in liver protein expression. […] It is likely that the full extent of the variation in CYP3A4 is still to be discovered […] While it is thought that CYP3A4 is not subject to an obvious major polymorphism, CYP3A5 definitely is. […] *3/*3 individuals form no serviceable CYP3A5. Functional CYP3A5 is found in around 20 per cent of Caucasians, half of Chinese/Japanese, 70 per cent of Hispanics and more than 80 per cent of African Americans.”
“A particularly dangerous polymorphism clinically was identified in the 1980s for one of the methyltransferases. The endogenous role of S-methylating thiopurine S-methyltransferase (TPMT) is not that clear, but […] [t]hese drugs are […] effective in some childhood leukaemias […] TPMT highlights the genotyping/phenotyping issue mentioned earlier in the management of patients with polymorphisms. Genotyping will reveal the level of TPMT expression that should be expected in the otherwise healthy patient. However, there are many factors which impact day-to-day TPMT expression during thiopurine therapy. […] Hence, what might be predicted from a genotype test may bear little resemblance to how the enzyme is performing on a particular day in a treatment cycle. So clinically, it is preferred to test actual TPMT activity.”
“Understanding of sulphonation and its roles in endogenous as well as xenobiotic metabolism is not as advanced compared with that of CYPs; however, the role of SULTs in the activation of carcinogens is becoming more apparent. One of the major influences on SULT activity is their polymorphic nature; in the case of one of the most important toxicologically relevant SULTs, SULT1A1, this isoform exists as three variants, SULT1A1*1 (wild-type), SULT1A1*2 and SULT1A1*3. The *1 variant allele is found in the majority of Caucasians (around 65 per cent), whilst the *2 variant differs only in the exchange of one amino acid for another. This single amino acid change has profound effects on the stability and catalytic activity of the isoform. The *2 variant is found in approximately 32 per cent of Caucasians and catalytically faulty […] About 9 in 10 Chinese people have the *1 allele and about 8 per cent have allele *2. About half of African-Americans have *1 and a third have *2. Interestingly, there is a *3 which is rare in most races but accounts for more than 22 per cent of African Americans. There is also considerable variation in SULT2A1 and SULT2B1, which are the major hydroxysteroid sulphators in the body, which may have implications for sex steroid and cholesterol handling. […] from the cancer-risk viewpoint, a highly active SULT1A1 *1 is usually an advantage in that it usually removes reactive species rapidly as stable sulphates. With some agents it is problematic as certain carcinogens such as acetylfluorene are indirectly activated to reactive species by SULTs. In addition, protective dietary flavonoids […] are also rapidly cleared by SULT1A1 *1, so there is a combination of production of toxins and loss of protective dietary agents. In terms of carcinogenesis risk, SULT1A1*2 could be a liability as potentially damaging substrates such as electrophilic toxins cannot be cleared rapidly. However, in some circumstances the *2 allele can be rather protective as […] it also allows protective agents [to] remain in tissues for longer periods. The combinations are endless and so it is often extremely difficult to predict risks of carcinogenicity for individuals and toxin exposures.”
“GSTs are polymorphic and much research has been directed at linking increased predisposition to cytotoxicity and carcinogenicity with defective GST phenotypes. Active wild-type GSTMu-1 is found in around 60 per cent of Caucasians, but a non-functional version of the isoform is found in the remainder. […] GST-M1 null (non-functional alleles) can predispose to risks of prostate abnormalities and GST Pi is subject to several SNPs and many attempts have been made to link these SNPs with the consequences of failure to detoxify reactive species, such as the risk of lung cancer. […] Carcinogenesis may be due to a complex mix of factors, where different enzyme expression and activities may combine with particular reactive species from specific parent xenobiotics that lead to DNA damage only in certain individuals. Resolving specific risk factors may be extremely difficult in such circumstances. […] in cancer chemotherapy, there is evidence that the presence of GST-M1 and GST-T1 null (non-functional) alleles predisposes children to a six-fold higher level of adverse events usually seen with antineoplastic drugs, such as bone marrow damage, nephrotoxicity and neurotoxicity.”
“The effects of age on drug clearance and metabolism have been known since the 1950s, but they have been extensively investigated in the last 20 or so years. It is now generally accepted that at the extremes of life, neonatal and geriatric, drug clearance can be significantly different from the rest of humanity. In general, neonates, i.e. those less than four weeks old, cannot clear certain agents due to immaturity of drug metabolizing systems. Those over retirement age cannot clear the drugs due to loss of efficiency in their metabolizing systems. Either way, the net result can be toxicity due to drug accumulation. […] It seems that the inability of older people to clear drugs is not necessarily related to the efficacy of their CYP-mediated oxidations, which are often not much different from that of younger individuals. Studies with the major CYPs in vitro have revealed that CYP2D6 is unaffected by age, as are most other CYPs, with the exception of CYP1A2, which does decline in activity in the elderly. […] In general, there is little significant change in the inducibility in most CYPs, or in the capability of conjugation systems in vitro. […] there are significant changes in the liver itself, as it decreases in mass and its blood flow is reduced as we age. This occurs at the rate of around 0.5–1.5 per cent per year, so by the time we hit 60–70, we may have up to a 40 per cent decline in liver blood flow compared with a 30-year-old. Other factors include gradual decline in renal function, increased fat deposits and reduction in gut blood flow, which affects absorption. […] The problem arises that the drug’s bioavailability increases due to lack of first-pass clearance; this means that from a standard dose, blood levels can be considerably higher than would be expected in a 40-year-old. This can be a serious problem in drugs with a narrow TI, such as antiarrhythmics. In addition, average doses of warfarin required to provide therapeutic anticoagulation in the elderly are less than half those required for younger people. The person’s lifelong smoking and drinking habits, as well as older individuals ’ sometimes erratic diet also complicate this situation. Among the drugs cleared more slowly in older people are antipsychotics, paracetamol, antidepressants, benzodiazepines, warfarin, beta-blockers and indomethicin.”
“Thousands of polyphenols are found in plants, vegetables, fruit, as well as tea, coffee, wine and fruit juices. […] Flavonoids such as quercetin and fisetin are excellent substrates for COMT, so competitively inhibiting the metabolism of endogenous catecholamine and catechol oestrogens. Quercetin and other polyphenols are found in various foods such as soy (genestein) and they are potent inhibitors of SULT1A1 which sulphate endogenous oestrogens, so potentiating the effects of oestrogens in the body. Many of these flavonoids and isoflavonoids are manufactured and sold as cancer preventative agents; however, it is more likely that their elevation of oestrogen levels may have the opposite effect in the long term. It is also likely that various polyphenols influence other endogenous substrates of sulphotransferases, such as thyroid hormones and various catecholamines. It is gradually becoming apparent that polyphenols can induce UGTs, indeed; it would be surprising if they did not. […] Overall, it is likely that there are a large number of polyphenols that are potent modulators of CYPs and conjugative enzymes. […] It is clear that diet can substantially modulate biotransformation […] As to the effects on prescription drugs, […] abrupt changes in a person’s diet may significantly alter the clearance of drugs and lead to loss of efficacy or toxicity.”
“In general, experimental or ‘probe’ drugs […] which are used to study the activities of a number of CYPs, are metabolized more quickly by women than men. This is allowing for differences in weight, fat distribution (body mass index) and volume of distribution […] It appears that CYP expression is linked to growth hormone (GH) and about the same amount is secreted over 24 hours in both sexes. In animals the pattern of release of the hormone is crucial to the effects on the CYPs; in females, GH is secreted in small but more or less continuous pulses, while males secrete large pulses, then periods of no secretion. The system is thought to be similar in humans. […] Little is known of the effects of the menopause and hormone replacement, where steroid metabolism changes dramatically. It is highly likely that these events could have profound effects on female drug clearance. […] females in general are more susceptible to drug adverse reactions than males, especially hepatotoxic effects.”
“For those chronically dependent on ethanol their CYP2E1 levels can be ten-fold higher than non-drinkers and they would clear CYP2E1 substrates extremely quickly if they chose to be sober for a period of time. This may lead to the accumulation of metabolites of the substrates. It is apparent that alcoholics who are sober can suffer paracetamol (acetaminophen)-induced liver toxicity at overdoses of around half that of non-drinkers, which is due to CYP2E1 induction. […] the vast variation in ADH [alcohol dehydrogenase] catalytic activity across the human race is mainly due to just a few SNPs that profoundly change the efficiency of the isoforms. ADH1B/*1 is the most effective variant and is the ADH wild-type […] Part of a ‘successful’ career as an alcoholic depends possessing the ADH1B/*1 isoform. The other defective isoforms are found in low frequencies in alcoholics and cirrhotics. […] in the vast majority of individuals, whatever their variant of ADH, they are able to process acetaldehyde to acetate and water, as the consequences of failing to do this are severe. With ALDH, the wild-type and gold standard is ALDH2*1/*1, which has the highest activity of all these isoforms and is the second essential component for an alcoholic career. […] the variant ALDH2*1/*2 has less than a quarter of the wild-type’s capacity and is found predominantly in Eastern races. The variant ALDH2*2/*2 is completely useless and renders the individuals very sensitive to acetaldehyde poisoning, although the toxin is removed eventually by ALDH1A1 which does not seem to be affected by polymorphisms. In a survey of 1300 Japanese alcoholics, there was nobody at all with the ALDH2*2/*2 variant. […] Women are much more vulnerable to ethanol damage and on average die in half the time it generally takes for a male alcoholic to drink himself to death. Women drink much less than men also – one study indicated that a group of women consumed about 14,000 drinks to induce cirrhosis, whilst men required more than 44,000 to achieve the same effect. Ethanol distributes in total body water only, so in women their greater fat content means that blood ethanol levels are higher than men of similar weight and age.“
I have had a look at two sources, the Office of Refugee Resettlement’s annual reports to Congress for the financial years 2013 and 2014. I have posted some data from the reports below. In the cases where the page numbers are not included directly in the screen-caps, all page numbers given below are the page numbers of the pdf version of the documents.
I had some trouble with how to deal with the images included in the post; I hope it looks okay now, at least it does on my laptop – but if it doesn’t, I’m not sure I care enough to try to figure out how to resolve the problem. Anyway, to the data!
The one above is the only figure/chart from the 2014 report, but I figured it was worth including here. It’s from page 98 of the report. It’s of some note that, despite the recent drop, 42.8% of the 2014 US arrivals worked/had worked during the year they arrived; in comparison, only 494 of Sweden’s roughly 163.000 asylum seekers who arrived during the year 2015 landed a job that year (link).
All further images/charts below are from the 2013 report.
It’s noteworthy here how different the US employment gap is to e.g. the employment gap in Denmark. In Denmark the employment rate of refugees with fugitive status who have stayed in the country for 5 years is 34%, and the employment rate of refugees with fugitive status who have stayed in the country for 15 years is 37%, compared to a native employment rate of ~74% (link). But just like in Denmark, in the US it matters a great deal where the refugees are coming from:
“Since their arrival in the U.S., 59 percent of refugees in the five-year population worked at one point. This rate was highest for refugees from Latin America (85 percent) and lowest for refugees from the Middle East (48 percent), while refugees from South/Southeast Asia (61 percent) and Africa (59 percent) were positioned in between. […] The highest disparity between male and female labor force participation rates was found for respondents from the Middle East (64.1 percent for males vs. 34.5 percent for females, a gap of 30 points). A sizeable gender gap was also found among refugees from South/Southeast Asia (24 percentage points) and Africa (18 percentage points), but there was hardly any gap among Latin American refugees (3 percentage points). Among all refugee groups, 71 percent of males were working or looking for work at the time of the 2013 survey, compared with 49 percent of females.” (p.94)
Two tables (both are from page 103 of the 2013 report):
When judged by variables such as home ownership and the proportion of people who survive on public assistance, people who have stayed longer do better (Table II-16). But if you consider table II-17, a much larger proportion of the refugees surveyed in 2013 than in 2008 are partially dependent on public assistance, and it seems that a substantially smaller proportion of the refugees living in the US in the year 2013 was totally self-reliant than was the case 5 years earlier. Fortunately the 2013 report has a bit more data on this stuff (p. 107):
The table has more information on page 108, with more details about specific public assistance programs.Table II-22 includes data on how public assistance utilization has developed over time (it’s clear that utilization rates increased substantially during the half-decade observed):
Some related comments from the report:
“Use of non-cash assistance was generally higher than cash assistance. This is probably because Medicaid, the Supplemental Nutrition Assistance Program (SNAP), and housing assistance programs, though available to cash assistance households, also are available more broadly to households without children. SNAP utilization was lowest among Latin Americans (37 percent) but much higher for the other groups, reaching 89 to 91 percent among the refugees from Africa and the Middle East. […] Housing assistance varied by refugee group — as low as 4 percent for Latin American refugees and as high as 32 percent for refugees from South/Southeast Asia in the 2013 survey. In the same period, other refugee groups averaged use of housing assistance between 19 and 31 percent.” (pp. 107-108)
The report includes some specific data on Iraqi refugees – here’s one table from that section:
The employment rate of the Iraqis increased from 29.8% in the 2009 survey to 41.3% in 2013. However the US female employment rate is still actually not much different from the female employment rates you observe when you look at European data on these topics – just 29%, up from 18.8% in 2009. As a comparison, in the year 2010 the employment rate of Iraqi females living in Denmark was 28% (n=10163) (data from p.55 of the Statistics Denmark publication Indvandrere i Danmark 2011), almost exactly the same as the employment rate of female Iraqis in the US.
Of note in the context of the US data is perhaps also the fact that despite the employment rate going up for females in the time period observed, the labour market participation rate of this group actually decreased between 2009 and 2013, as it went from 42.2% to 38.1%. So more than 3 out of 5 Iraqi female refugees living in the US are outside the labour market, and almost one in four of those that are not are unemployed. A few observations from the report:
“The survey found that the overall EPR [employment rate, US] for the 2007 to 2009 Iraqi refugee group in the 2013 survey9 was 41 percent (55 percent for males and 29 percent for females), a steady increase in the overall rate from 39 percent in the 2012 survey, 36 percent in the 2011 survey, 31 percent in the 2010 survey, and 30 percent in the 2009 survey. As a point of further reference, the EPR for the general U.S. population was 58.5 percent in 2013, about 17 percentage points higher than that of the 2007 to 2009 Iraqi refugee group (41.3 percent). The U.S. male population EPR was nine percentage points higher than the rate for Iraqi males who arrived in the U.S. in 2007 to 2009 (64 percent versus 55 percent), while the rate for the Iraqi females who arrived in the U.S. in 2007 to 2009 was 24 points higher for all U.S. women (53 percent versus 29 percent). The difference between the male and female EPRs among the same group of Iraqi refugees (26 percentage points) also was much larger than the gap between male and female EPRs in the general U.S. population (11 points) […] The overall unemployment rate for the 2007 to 2009 Iraqi refugee group was 22.9 percent in the 2013 survey, about four times higher than that of the general U.S. population (6.5 percent) in 2013” (pp. 114-115).
“To date, no prospective study has directly compared the efficacy and tolerability of selective serotonin reuptake inhibitors (SSRIs), serotonin/ norepinephrine reuptake inhibitors (SNRIs), or other second-generation antidepressants in patients with diabetes versus patients without diabetes.”
“Weight is a common and well-known adverse effect of short-term and long-term treatment with TCAs, primarily as a result of excessive appetite. […] weight gain is the most common cause for premature discontinuation of all TCAs. […] TCAs are […] likely to impair diabetes control, because they increase serum glucose levels by up to 150%, increase appetite (particularly carbohydrate craving), and reduce the metabolic rate. […] SSRIs have been associated with both weight gain and weight loss. […] Weight gain is less likely with SSRIs when they are used short term — for 6 months or less. Contradictory evidence exists about whether an increase in body weight occurs in patients using SSRIs for 1 year or longer. […] The mean incidence of weight gain across comparative randomized controlled trials ranges from 4.1% for fluoxetine, 7.6% for sertraline, and 9.6% for paroxetine. […] SSRIs may reduce serum glucose by up to 30% and cause appetite suppression, resulting in weight loss. Fluoxetine should be used cautiously in patients with diabetes, because of its increased potential for hypoglycemia […]. Its side effects of tremor, nausea, sweating, and anxiety may also be misinterpreted as due to hypoglycemia.”
“Prior to the development of the second-generation antipsychotics (SGAs), or atypical antipsychotics, phenothiazines were the dominant therapy for schizophrenia. Numerous studies at this time began documenting that the use of phenothiazines led to aggravation of preexisting diabetes and the development of new-onset type 2 diabetes. […] high-potency neuroleptics […] appeared to be less implicated in the development of diabetes. These drugs eventually became the predominant form of therapy for schizophrenia […] Unfortunately, the high-potency neuroleptics are also associated with a high rate of occurrence of extrapyramidal symptoms, tardive dyskinesia, and subsequent noncompliance […] In the late 1980s, a new class of antipsychotics, the thiobenzodiazepines or “atypical antipsychotics,” was introduced. […] One major advantage of these agents was a marked reduction in the occurrence of extrapyramidal symptoms. […] However, the atypical antipsychotics have also proven to carry their own unique side-effect profile. Side effects include substantial weight gain […] lipid abnormalities […] Hyperglycemia and diabetes are strongly associated with some of the newer atypical antipsychotics […] Thus, many psychiatrists are finding themselves in the difficult position of trading efficacy in the treatment of schizophrenia for an array of adverse metabolic side effects.”
“Weight gain is one of the more noticeable effects of all of the psychotropics. Although the SGAs appear to be a major culprit, TCAs, lithium, and mood stabilizers such as valproic acid or divalproex sodium and carbamazepine are also associated with weight gain. […] A range of evidence suggests that treatment with certain antipsychotic medications is associated with an increased risk of insulin resistance, hyperglycemia, and type 2 diabetes, compared with no treatment or treatment with alternative antipsychotics. […] A growing body of evidence supports the key observation that treatments producing the greatest increases in body weight and adiposity are also associated with a consistent pattern of clinically significant adverse effects on insulin resistance and changes in blood glucose and lipid levels. However, there are a growing number of cases of antipsychotic-associated hyperglycemia that involve patients without substantial weight gain, and reports that involve patients who improve when the offending agent is discontinued or who experience deterioration of glycemic control when re-challenged with the drug. […] Antipsychotics may lead to diabetes in susceptible individuals by causing decreased insulin secretion, increased insulin resistance, or a combination of both. Data suggest, however, that insulin resistance is primarily the responsible mechanism. […] The mechanism through which antipsychotics lead to insulin resistance is not clear.”
“Many drugs may influence glucose insulin homeostasis. Commonly prescribed drugs that may have adverse effects on carbohydrate metabolism, especially in patients with diabetes mellitus or those at risk of developing glucose intolerance, include diuretics, beta-blockers, sympathomimetics, corticosteroids, and sex hormones”.
The book’s Table 4.11 include a really nice list of drugs, or drug classes, that can increase blood glucose levels, which includes quite a few commonly used drugs. A couple of to me surprising culprits on that list were marijuana and oral contraceptives; the oral contraceptives one certainly makes a lot of sense in retrospect (I don’t really know much about the metabolism of marijuana/cannabis, all I’ve ever learned about that stuff includes what was covered in the appendix of Coleman’s excellent textbook – and I have no personal experience…), I just hadn’t thought about the fact that very commonly used drugs like these may also have side effects of this nature).
“Patients with depression or bipolar depression may lack interest in their well-being and suffer from difficulty maintaining focus. Furthermore, many depressed patients suffer from decreased energy, psychomotor retardation, and changes in appetite, which may further promote weight gain. All of these make it very challenging to successfully implement a weight loss program in depressed patients. […] In addition, many patients with mental illnesses such as depression […] often state that eating is one of the few highlights of their day.” (So it’s probably a good idea to avoid giving these people drugs which will cause them to gain a substantial amount of weight/increase appetite/increase carbohydrate cravings, to the extent that this is possible…)
“Diabetes is considered a coronary artery disease equivalent by the National Cholesterol Education Panel (NCEP) […] Aspirin therapy is considered a routine part of secondary prevention in people with diabetes and a history of cardiovascular disease, and it is also recommended as part of primary prevention for cardiovascular disease in all patients with diabetes older than 40 years of age; additionally treatment with 75 to 325 mg/day of aspirin should be considered in patients 30 to 40 years of age with one additional cardiovascular risk factor.1,13 […] for all people older than 40 years of age with diabetes, statin therapy is recommended to lower the LDL by 30% to 40%, regardless of baseline levels.14 […] Lowering triglycerides to levels less than 150 mg/dL also confers cardiovascular benefit.1,14 However, hyperglycemia and hypertriglyceridemia are intricately linked, likely through elevations of free fatty acids. Free fatty acids are potent inhibitors of insulin action and transport, and act to disrupt glucose transport into skeletal muscle. Thus, triglyceride goals are often difficult to attain in uncontrolled diabetes.”
In some weird way some aspects of the last part of the book’s coverage was quite funny. So you have a diabetic whose disease has caused extensive damage to the nervous system leading to painful neuropathy. How do you treat the (in general difficult to treat) symptoms of neuropathy? Why, you give him tricyclic antidepressants (which will of course make his diabetes harder to treat, and cause him to gain weight). No, I’m not making this up:
“The most widely used medical treatments for symptoms of diabetic neuropathy include gabapentin and tricyclic antidepressants.”
Or how about this one – you have a type 2 diabetic who’s most likely overweight and who could probably benefit quite a bit from losing weight; why, let’s treat his diabetes with a drug that causes him to gain weight! People actually do this: “Thiazolidinediones (rosiglitazone, pioglitazone) act as agonists of the peroxisome proliferator-activator receptor gamma and improve insulin sensitivity at the tissue level. These agents are contraindicated in patients with heart failure and can worsen peripheral edema. Unfortunately, a common side effect of the glitazone class of agents is weight gain.” They’re not first-line agents, but they are used in diabetics. Just to make things even better, these drugs also seem to increase the risk of osteoporosis, a risk which is already somewhat elevated in type 2 diabetics: “Additionally, these drugs [thiazolidinediones] appear to decrease appendicular bone mass with associated increased risk of fractures.34“
…or perhaps now some people might start thinking here: ‘Is stuff like this actually part of the explanation for Vestergaard’s findings described in the link above?’ I should add to these people that this is unlikely to be the case, especially considering the big difference between the (really quite substantial) type 1- and (significantly lower) type 2 fracture risk elevation; thiazolidinediones are not used in the treatment of type 1, and it’s not even a first-line treatment of type 2 – other explanations, such as those covered in Czernik & Fowlkes’s text, seem much more likely to matter (though in the context of a few individuals these drugs may still be of relevance).
“In addition to glycemic goals, nonglycemic treatment goals of blood pressure control, lipid management, and initiation of aspirin therapy are often necessary. For many patients, the diagnosis of diabetes results in multidrug therapy. For patients with mental illness who are likely to already be on multiple medications, the addition of several new agents can be difficult. Several studies have suggested that medication adherence in patients with psychiatric illness is poor at baseline,38 and may worsen when an increasing number of medications are prescribed.”
It’s also worth remembering here that “asymptomatic and chronic diseases needing long-term treatment […] result in poorer compliance”, although on the other hand “patient-controlled non-compliance [is] lower in treatment for diseases in which the relationship between non-compliance and recurrence is very clear, such as diabetes, compared to treatment for diseases in which this relationship is less clear” (Kermani and Davies). Combine psychiatric disease with chronic illnesses of a different kind and potential polypharmacy and non-compliance certainly becomes an issue worth taking into account when considering what might be the optimal treatment regime. It’s also worth keeping in mind that even in people without psychiatric problems adherence tends to be low in the case of antihypertensives and lipid-lowering drugs – again I refer to Kermani and Davies’ text:
“Chapman et al. (2005) recently examined compliance with concomitant antihypertensive and lipid-lowering drug therapy in 8406 enrollees in a US-managed care plan […] Less than half of patients (44.7 per cent) were adherent with both therapies three months after medication initiation, a figure that decreased to 35.8 per cent at 12 months.”
No other interpretation of this piece even comes close to Zimerman’s, in my opinion. This is as good as it gets.