This is a Wiley-Blackwell publication about human nutrition. It is also perhaps the strangest W-B publication I’ve ever read, because of the combination of the following two facts: i. Each chapter is two pages long (the book has 62 chapters). ii. This is an academic text without a single source or reference. The latter of those two points is the main reason why I have not rated the book.
The chapters are denser than you’d think (they have a lot of information considering what you’d expect from two-page chapters), and many chapters ‘come in pairs’ or deal with related stuff; for example there are three main chapters dealing exclusively with proteins – one about the ‘chemistry and digestion’ of proteins, another one about the ‘functions of proteins in the body’, and a third one about the ‘needs and sources’ of proteins. Carbohydrates and fats also get multiple chapters each, and micronutrients get 7 chapters of ‘exclusive coverage’ dealing only with those things. The level of detail is reasonably high (again considering what you’d expect), but of course there’s only so much stuff you can cram into a chapter two pages long. I think in many ways it is a really neat book to have for looking up stuff in this area that you’re wondering about and/or can’t quite remember (‘what was the role of butyric acid in the colon again?’ ‘Which factors affect calcium absorption?’ ‘What are the roles of the various B-vitamins in metabolism? How might I get into trouble if I don’t get enough riboflavin, and what can I do to avoid that situation?’). Quite a few of the things she talks about I don’t really consider it too problematic that she does not source; she knows a lot more about which role folate plays in the regulation of homocysteine levels than I do, and I don’t think there’s a big risk involved in just taking her word for it that those things work the way she says they do. Much of the book covers stuff on a level where I could justify thinking along such lines; many of the chapters are a bit like book versions of short Khan Academy nutrition lectures (perhaps a bit like lectures like this and this, I guess without having watched those lectures), and I figure if I’m okay with watching lectures like those I should be okay with reading a book like this as well, which is a big part of the reason why I didn’t just throw it away the moment I realized that there was actually not a single page of references to be found anywhere.
As I didn’t rate the book because of it, the lack of sourcing of course bothered me. One thing which puzzled me is why she decided to write the book this way – I simply do not understand that decision at all. Given the current state of affairs of nutritional science (and the current state at the time the book was written in 2007), I will say that I think the way she has chosen to write this book is simply flabbergasting to me. Nothing tempts people to disregard your information like not telling them where it comes from. There is not a single sentence in this book with the words ‘[X & Y] found that…’ – she only ever writes ‘a study found that…’, and this is just infuriating. There are various recommendations of daily intake of various substances in the book, but you have no idea who came up with those recommendations or which evidence base they are based on – there’s not even a source indicated in the headings in those cases. I simply don’t understand why she’d write the book that way – the lack of sources makes much of the stuff look deeply suspect, regardless of whether or not it’s actually all of it based on ‘the best available evidence’, and occasionally it seems as if she’s gone out of her way to avoid adding a source even in situations where it would make a lot more sense to add it than to not do that. To add insult to injury, a couple of the reported estimates in the last half of the book were so out of line with other estimates I could find elsewhere that I seriously considered throwing the book away. So, yeah.
But the book has a lot of good stuff as well which presumably a lot of people would benefit from knowing about, so it’s really hard for me to know what to think about it. To take an example of what I’m talking about here, Rees et al. observed in their book – as I have pointed out – that: “Vegans who omit all animal products from their diet often have subclinical vitamin B12 deficiency.” They probably wouldn’t have if they’d read this book. Anemia is a very common condition worldwide, and iron deficiency is estimated to be the most common cause. An estimated 250 million preschool children are vitamin A deficient. We humans need a lot of different stuff to keep going, and the food we eat plays many roles most of us probably haven’t given any thought. Everybody needs to eat, so there aren’t many people who would not benefit from knowing more about how these things work; even people following ‘an ideal balanced diet’ can be at risk of developing deficiency states due to malabsorption syndromes or various disease states which may change nutritional requirements.
I’ve added some ‘sample observations’ from the book, as well as a few comments, below:
“There is a continuous turnover of protein in the body, which in healthy adults exhibits a balance between synthesis and breakdown, and amounts to 3–6 g/kg body weight per day. During growth there is an excess of synthesis over breakdown, and in wasting conditions (e.g. starvation, cancer and after surgery or trauma), breakdown exceeds synthesis. Protein synthesis is regulated principally by insulin, and catabolism by glucocorticoids. […] The body is unable to make nine of the amino acids used in protein synthesis […] Lack of any one of these will limit the synthesis of protein, even if all the other required amino acids are present in adequate amounts. […] In addition, there are a number of other amino acids that can be synthesised in the body under normal conditions, given the necessary supply of precursor molecules. In the absence of these precursors, the amino acids become ‘conditionally indispensable […] Protein synthesis is an energy-demanding process; it has been calculated that the energy requirement is 4.2 kJ (1 kcal)/g of protein synthesised. Protein synthesis occurs more rapidly after a meal than in the fasting state, due to the greater supply of amino acids. On average the energy used in protein synthesis accounts for 12% of the basal metabolic rate. […] The digestibility of proteins from animal sources is much greater than that from plant sources. Digestibility for egg is given as 97%. […] Poor digestibility, of between 60 and 80%, is found in legumes and cereals with tough cell walls, particularly when uncooked, and is a factor in diets that are low in protein. […] Worldwide, the availability of plant proteins is relatively consistent, at about 50 g/person/day. However, the availability of animal protein sources varies widely, from <5 to 50 g/head/day, highest in most Western countries. […] Inadequate protein intakes rarely occur alone, and are generally found within a wider picture of undernutrition. Insufficient intakes of energy cause protein to be used for energy, and make it unavailable for tissue maintenance or growth.”
“The most rapid period of brain growth occurs from mid-gestation to 18 months after birth. At birth the brain accounts for 10% of the body weight; an adult brain weighs about 1.4 kg, and comprises 2% of body weight. Different components of the brain grow at different rates and have ‘critical periods’ when growth is most rapid and vulnerable to adverse influence.”
‘Alcohol and folic acid’ would probably be two factors most people would know about in this context. But there’s of course a lot more to developing a human brain than these variables. Generalized undernutrition can lead to smaller brain and less extensive neural networks, long-chain polyunsaturated fatty acids are quite important for brain development, you need copper for myelin synthesis but too much of it may be toxic, iodine deficiency leads to cretinism, severe iron deficiency may lead to long-term reductions in cognitive performance whereas too much of it again may lead to toxicity, excess vitamin A intake may be teratogenic, pyridoxine deficiency may lead to seizures/neurologic symptoms, … Incidentally the arrow doesn’t just go from food intake to brain performance; the brain is also helping you figure out what to eat: “neurotransmitters acting within the brain are thought to regulate preferences for particular macronutrients. Serotonin may influence the balance between carbohydrate and protein intakes. Noradrenaline and opiates are also believed to have a role. […] Disturbances of neurotransmitter release, whether of endogenous (e.g. in disorders of brain function) or exogenous origin (e.g. by drugs), are likely therefore to affect food intake.”
Some more stuff about childhood growth from a few chapters on related matters:
“The fastest rate of growth is in the first 6 months of life, with a doubling of birth weight, and slows towards 12 months, to achieve about three times birth weight. Body weight only doubles between the ages of 1 and 5 years. Standard growth charts are useful to check that growth is progressing appropriately […] During the years of [school-age] childhood, mean growth is relatively constant, and averages 2.5 kg and 6 cm per year. During puberty, on average: • girls increase by 20 cm (height) and 20 kg (weight); • boys increase by 30 cm (height) and 30 kg (weight). These increases represent 40% of eventual adult weight. Growth is vulnerable to faltering if nutritional intakes do not keep pace with the demands. […] Body fat percentage levels increase rapidly in the first months of life, but start to fall after the first year. […] There is a further increase from about the age of 5 years (adiposity rebound), which may start earlier in larger, fatter children […] In boys, the fat content starts to fall during the pubertal growth spurt, but in girls it continues to increase, resulting in the average 10% fat content differential between the sexes seen in adults. […] Growth in infants and young children, usually recorded as weight, should progress along a centile line on standard growth charts. Reasons for centile crossing (moving from one centile line to another) need to be established. […] Infants of diabetic mothers, who are often born very large (>4.5 kg), may exhibit ‘catch-down’ growth during the first year of life. Once removed from the oversupply of nutrients in the womb, their growth rate slows. […] An infant undernourished in the womb may show ‘catch-up’ growth. This should be an increase in lean body mass, rather than fat; the latter is linked to risk of later disease.”
“It is now recognised that vitamin D is synthesised in the skin by the action of ultraviolet light on a precursor, and could strictly be termed a hormone rather than a vitamin. Further, niacin [vitamin B3] can be made in the body from the amino acid tryptophan, so a separate supply may not be needed if protein intakes are adequate. However, in both of these cases, there are situations where synthesis is insufficient, and so a dietary need remains.”
“Inadequate intakes of macronutrients will most obviously be reflected in disturbed growth in children and body weight changes in adults. […] Undernutrition in the elderly is poorly reported, but is believed to be widespread […] The consequences of undernutrition can manifest both in the short and long term, and may have intergenerational effects, through poor pregnancy outcome and low birth weight. […] Worldwide, deficiencies of iron, vitamin A and iodine affect the greatest numbers of people. […] Several other micronutrients may become deficient when diets lack specific food groups. These include: • vitamin B12, when vegan diets are consumed; • calcium, when dairy products are excluded from the diet; • riboflavin, when diets are low in green vegetables and dairy products.”
“The typical increase in weight (in the UK) during pregnancy is 11–16 kg but varies widely. Gains in the second and third trimesters should average 0.4 kg/week for normal weight women, less (0.3 kg/ week) for overweight women and more (0.5 kg/week) for women who are underweight. […] The extra energy costs of pregnancy are estimated at 310 MJ (77 000 kcal) […] The mother’s nutritional status is unlikely to affect the volume or the macronutrient content of her milk for the first few weeks of lactation. However, poorly nourished women will not be able to sustain the same level of nutrients for prolonged periods. The fat content of the milk correlates with the mother’s levels of body fat, and the pattern of fatty acids secreted in the milk partly reflects those in the mother’s dietary intake. Neither the fat-soluble vitamin content nor the mineral content of the milk fluctuates with maternal dietary intake.”
“ATP is the fundamental molecule that on breakdown to ADP provides energy for contracting muscle. ATP stores are very limited and require continual replenishment; the amount stored would fuel only about two seconds of exercise. […] CHO [Carbohydrate] stores in muscle (300–800 g) and liver (80 g) are limited; fats stored mainly in subcutaneous tissue are found in very much greater amounts (minimum 5 kg in males, more in females). • Lipids are considerably more energy dense than CHOs. Metabolism of one gram of fat will deliver considerably more ATP molecules than one gram of CHO; however, more oxygen is required to metabolise fats, and fats cannot be metabolised anaerobically […] An important principle is that carbohydrates are the preferred energy source particularly for more intense and prolonged exercise […] Most athletes already consume sufficient protein in a mixed diet […] With the exception of energy intake the evidence that normal dietary supplements enhance sporting performance is poor.”
I found the two chapters about nutrition and sport interesting in a way, but mostly because they helped me figure out what happens in normal people – a book like this (which I have considered reading in the past, but has never gotten around to actually reading) is probably better at elucidating relevant mechanisms in my case.
“Consumers generally believe that foods produced organically, often by more traditional agricultural methods, have superior nutritional quality. This is not currently supported by the scientific literature, in which studies find no difference in nutrient content between organic and non-organic produce; there is also no information about impact on human health.”
“Thirty-five percent of U.S. adults say that at one time or another they have gone online specifically to try to figure out what medical condition they or someone else might have.
These findings come from a national survey by the Pew Research Center’s Internet & American Life Project. Throughout this report, we call those who searched for answers on the internet “online diagnosers”.
When asked if the information found online led them to think they needed the attention of a medical professional, 46% of online diagnosers say that was the case. Thirty-eight percent of online diagnosers say it was something they could take care of at home and 11% say it was both or in-between.
When we asked respondents about the accuracy of their initial diagnosis, they reported:
41% of online diagnosers say a medical professional confirmed their diagnosis. An additional 2% say a medical professional partially confirmed it.
35% say they did not visit a clinician to get a professional opinion.
18% say they consulted a medical professional and the clinician either did not agree or offered a different opinion about the condition.
1% say their conversation with a clinician was inconclusive.
Women are more likely than men to go online to figure out a possible diagnosis. Other groups that have a high likelihood of doing so include younger people, white adults, those who live in households earning $75,000 or more, and those with a college degree or advanced degrees.”
The quotes above are from a Pew report, Health Online 2013, published earlier this year. Below I’ve added some more data from the report, as well as a few comments. You can click the tables to view them in a higher resolution.
“Looking more broadly at the online landscape, 72% of internet users say they looked online for health information of one kind or another within the past year. […] 77% of online health seekers say they began at a search engine such as Google, Bing, or Yahoo. Another 13% say they began at a site that specializes in health information, like WebMD. Just 2% say they started their research at a more general site like Wikipedia […] 39% of online health seekers say they looked for information related to their own situation. Another 39% say they looked for information related to someone else’s health or medical situation. […] As of September 2012, 81% of U.S. adults use the internet and, of those, 72% say they have looked online for health information in the past year. [Incidentally, according to this Pew report, the number of online Americans is actually 85%, but it’s in that neighbourhood… Note that 72% of 81% is just 58% (they say 59% in the report later, probably due to rounding) – so almost half of all Americans don’t look for health information online. That’s a lot of people.] […]
Females are more likely to be online diagnosers, as are young people, whites, rich people, and college-educated individuals (when we compare the females with males, the young people with the old, the white people with the non-white, etc. See also the remarks in the update..). Note that education is basically a step-function here; the more education you get, all else equal the more likely you are to try to diagnose yourself online. Note also that some of these differences are really huge; roughly 10 percent of people without a HS diploma answered that they’d looked online to diagnose a condition during the last year, whereas half of all college-educated individuals answered in the affirmative.
A potentially important thing to have in mind when comparing the numbers for insured and uninsured individuals is that internet usage and health insurance status probably covary; I believe it’s likely that uninsured people are also less likely to use the internet. Low-income individuals with short educations are much less likely to be online, independent of age (see the link above).
“Twenty-six percent of internet users who look online for health information say they have been asked to pay for access to something they wanted to see online. […] Of those who have been asked to pay, just 2% say they did so. [I was very surprised that that number was strictly larger than zero…] Fully 83% of those who hit a pay wall say they tried to find the same information somewhere else. Thirteen percent of those who hit a pay wall say they just gave up. […] Respondents living in lower-income households were significantly more likely than their wealthier counterparts to say they gave up at that point. Wealthier respondents were the likeliest group to say they tried to find the same information elsewhere.”
Do remember when looking at the numbers above that health status and education are related variables; lower educated people are more likely to be in poorer health than are higher educated people on average, in part because of lifestyle choices (I’ve written about these differences before – see e.g. this post (and note that there’s a lot of stuff in those links – and that I have a lot more links for you if you don’t find them satisfactory, as I’ve done academic work in this field and am quite familiar with the literature on the links between education and health.)). Yet even when conditioning on online status (low-educated individuals are less likely to be online), individuals with low educations are still, all other things being equal, much less likely than are the college educated to look online for many types of health information.
Update: To illustrate how much trouble you might get into if you don’t have in mind the differences in internet adoption rates across social strata, I decided to add a few more numbers. The numbers are from the Offline Adults report, to which I also link above:
People without a high school diploma are roughly 10 times as likely not to use the internet as are people with a college degree; 41% of people without a HS diploma don’t use the internet – 4% of college-educated don’t. For individuals with an income below $30k, one in four don’t use the internet, whereas roughly 5% of those with an income north of $50k don’t. It’s very safe to say that not all subgroups included in some of the specific types of response data above are equally representative of the groups from which they are derived. Note also that potential drivers of the relevant intragroup differences here may be very important if one were to try to find ways to ‘bridge the information gap’; for example if some of the low-educated individuals who don’t use the internet can’t read, finding ways to provide them with internet access may not make much difference.
I should point out here that based just on the observations above it’s impossible to say anything about the details of what drives these results. It’s not clear e.g. how big a role the age variable plays when it comes to the contribution from income and education; old people on a pension have much lower incomes (but higher net savings) than most people who’re still active in the labour market (link), and older people are also significantly less likely to have college degrees and more likely to not have a high school diploma. The significance tests they report which are meant to indicate whether or not e.g. the results for people with an income of $30-50k are different from the results for people with incomes below $30k don’t take stuff like that into account, they’re just of a ‘let’s ignore everything else and compare the numbers’-kind and so can’t really be trusted. Maybe income doesn’t matter once you’ve taken age and education into account. I’m not saying this is the case, but given the data you can’t say if that’s true or not. Disentangling the ‘pure partial effects’ would be nice, but that’s likely to be a lot harder than it looks; multicollinearity is likely a problem, and some of the correlated regressors display non-linear relationships (e.g. income-age – see the link above). Be careful about which conclusions you draw.
I’m currently writing a topic on ‘the causal effect of education on health’, so this is a topic I’ve looked at a bit – consider this post a ‘workblog’-post, even though it’s only tangentially related to what I’m working on.
This kind of stuff – health disparities related to education and income – pops up in the public debate every now and then, see e.g. this recent article (in Danish), or this analysis by AE-rådet (also in Danish). This is ‘politics’ to some extent (see the previous post), but it’s also a question about what’s actually going on in the world, and the latter type of question is the type of question I tend to be interested in answering. I’d like to make some general points here which are sometimes overlooked:
i. People with lower education are fatter. And being fat is bad for your health.
ii. People with lower levels of education smoke more: “Well-documented declines in smoking prevalence over time have not occurred evenly throughout society (12, 13). They have been most substantial among the most educated. Thus, the least educated form increasing proportions of those who remain smokers.” Regarding alcohol the picture is more complicated (as I’ve talked about before), however it should be noted that if the variance of the quantity consumed by the highly educated is lower than for the lower educated groups, as they claim in the article I link to at the beginning of this paragraph, then it would make sense if the highly educated people who die from alcohol-related diseases die later and lose fewer years of their life to the alcohol than does the group with low education (‘the uneducated alcoholic loses 20 years, the educated alcoholic loses five…’). Either way alcohol matters much less than smoking, and the differences aren’t that big in the former case. Incidentally the causal pathways of the smoking link are still unclear: “The causal pathways between education and smoking are both complicated and contested in the literature.” (link)
iii. Lifestyle differences among different educational groups make up a big part of the difference in health outcomes: “the mediating effects of health behaviors – measured by smoking, drinking, exercising and the body mass index – account in the short run for 17% to 31% and in the long run for 23% to 45% of the entire effect of education on health, depending on gender.”
iv. An additional point related to point iii.: I haven’t looked for studies on this because it’s obvious, but the health gradient is more sensitive to stuff like income level and employment status in countries like the US than it is in Denmark. So international (non-Scandinavian?) estimates of the magnitude of educational effects and income effects on health outcomes are likely to be biased upwards, compared to what the magnitude would be in a country like Denmark where ability to pay for medical services problems are unlikely to have much influence on life expectancy at this point.
v. I’ll spell out this point even though it should be obvious by now: Many of the reasons why people with a low education on average die too soon relate to the fact that they on average make poorer choices when it comes to their health. And the stuff mentioned above is just a small part of what’s going on; you also have related stuff like information channels and compliance differences, on top of stuff like ‘likelihood of seeking proper medical attention conditional on you actually needing it, and ability to verbalize complaints so that the doctor makes the correct inferences’ (e.g. a lot of T2 diabetics don’t get diagnosed, and this lowers their life expectancy significantly).
vi. Note that whereas it’s true that some jobs are still more unhealthy than others (a traditional mechanism most people think of when they’re thinking about these things), if the connection between type of work and health risks is known people employed in such jobs would be expected to earn a risk premium – this is not super relevant when you look at education and health, but it is something to have in mind when analyzing health and income stuff.
vii. It should be noted that if you get better over time at treating people for stuff that isn’t lifestyle-related and so stop a lot of people from dying early on of other causes, then lifestyle-stuff is going to become a big driver of health disparities.
“what kind of stories should we be suspicious of? Again I’m telling you, it’s the stories very often that you like the most, that you find the most rewarding, the most inspiring. The stories that don’t focus on opportunity cost, or the complex unintended consequences of human action. Because that very often does not make for a good story.”
We use narratives to explain stuff. We need an explanation we can understand and if there isn’t one, we will make one up. And we much prefer to believe stuff that is comfortable for us to believe is true. It goes for all areas of life, not just the ones one like to think about. I’ve picked out a few examples but you’re free to add to the list.
Non-smokers and non-drinkers will generally underestimate how hard it is for people who are drinking or smoking to stop drinking or smoking. The convenient story for the non-smoker or non-drinker is about how people who smoke or drink are weaker people (and therefore less deserving). Or perhaps they are less smart, because they could have just never started in the first place. On the other hand some of the people who smoke or drink a lot like to tell themselves that they are not addicted (because addiction will often imply weakness in the mental model applied to the problem) or that they have just as much willpower as the non-smoker/-drinker has, which would become obvious if the latter also smoke/drank as much as them. Notice that there may be multiple, perhaps conflicting, ways to construct a convenient narrative that makes you look good, not just one; it’s both possible for you as a smoker to convince yourself that you’re not addicted and thus isn’t a weak person (‘only weak people become addicts’), and it’s possible for you to convince yourself that you are addicted, but that the addiction means precisely that you’re not weak ‘because if someone as strong and great as you can become addicted, eveybody can’.
People who are not overweight will generally emphasize the importance of their own actions when explaining why they are not overweight and downplay other factors, whereas people who are overweight will often be more comfortable thinking in terms of factors over which they have little to no influence (like genetics). So the person who is not overweight will end up telling himself a convincing and convenient story about how he’s not overweight because he’s doing all the right things while disregarding other factors that may be quite important too, and by telling the narrative that way he may think of himself as a better person than the people whom he think do not behave the way he does, and/or he may think of himself as a better person than the people who do in fact behave in a similar manner, but have gotten different results from the diet- and exercise regime than he has gotten and thus have ended up overweight. The overweight guy will often tell a completely different story, which is just as compelling and convenient to him as the other story is to the non-overweight guy; he’s overweight because of his genes, because of his metabolism, because of his big bones, or perhaps because of his job that makes it hard for him to find time to exercise. He may think he’s better than the other guy because he works harder (or he would have time to exercise), or he may think he’s better because he does not, he tells himself, judge people by their appearance. The more general story about the blameless victim vs the deserving winner can be applied to all areas of life; if people have done well, it’s always because of stuff they did, and if they haven’t done well, nothing they could have done would have made any difference. That is, this is the story most of them will tell you if you ask them. Because that’s the story they tell themselves, and sometimes have told themselves for many years. (Things get more interesting if people can’t decide if they’ve done well or not.)
Often when people engage in political arguments, they downplay the arguments against the position they are defending. And they like political positions which make them look more deserving, make it look obvious that they should have a larger share of the pie. If reality will not play ball that’s often not a problem in political debates; in politics reality is just what people can agree is true. So when arguing about whether the people I like (‘people (/who) like me’) deserve to be in the position they are in, you can claim ‘it’s because of X’ and as long as a lot of people agree with you then X is considered a valid explanation. Note that the most convenient story always has a bad guy, and that in politics the convenient bad guy is almost always the guy who disagrees with you. Note also that in all the narratives you tell yourself, you’re the good guy. And this is the case for everybody else too.
When people think about what motivations others have for doing the things they do, they will often be tempted to try to explain the behaviour of others in terms of reactions to their own behaviour. They will tend to go for explanations involving them first if they can make one such explanation make them look good. ‘If she’s behaving nicely towards me, it must mean that I’m a nice person’ or ‘she’s behaving that way because I deserve to be well treated’. If it’s hard to come up with such an implicit explanation that makes one look good one will be more likely to find and include ‘external factors’ in the model; if she was angry it was not because of anything I did, rather it was because her boss is a silly old man, or because she’s on her period. This model even works when she explains that her anger is caused by something you did: If she’s told you that her anger was because you didn’t clean the house yesterday, you’re quite likely to at least partially disregard that explanation and find another one that better fits the image of you as the perfect husband; either one that does not involve you at all, or perhaps one that does involve you but also ‘shows’ just how unreasonable she is (‘She is probably still mad about that $300 overcoat I bought without asking her first. I should be allowed to buy an overcoat for myself without asking that crazy lady first, dammit!’). And when people tell themselves such narratives one of the funny things is that they both know that she is right (he should have cleaned the house), but they still hold on to the self-serving explanations in order to justify their own actions though they know that
they probably should not do this the partner disapproves of the behaviour. It makes sense though; we’re programmed to constantly look out for subtle ways to do a little less than our ‘fair share’, and you can’t cheat on others as well if you feel really bad about it afterwards and/or if you cannot catch up on the fact that your behaviour might be over the line. Incidentally, chimps have strong views on fairness stuff too.
Now, some of the stories humans made up in the past to explain the stuff we liked to explain back then doesn’t do very well today, when taking all the knowledge that is available to us at this point into account. Stories made up by people who died a long time ago still make up most of the religious texts around today, and you can tell if you read them. But it’s very often inconvenient for religious people to pick a different narrative, it’s in fact often very costly – and once again ‘reality’ is to a great extent just what people around you can agree with you is true. But people without religion do not do without competing convenient narratives; they will probably often tell themselves that they are smarter people for not believing stupid things. Or they will tell themselves that it’s all because of their own actions and ideas that they don’t believe in the stupid narratives, rather than it being to a great extent perhaps just a matter of being born by the right parents in the right century in the right country and being of the right gender (females are generally more likely to be religious than males).
It’s worth mentioning that not all self-serving stories are necessarily untrue or inaccurate. The degree to which such narratives are true or not will often depend upon your own point of view, but this is rather beside the point; the point is that people tell these narratives whether they are true or not, and the accuracy of the narrative often doesn’t much enter the equation in the first place. Sometimes self-serving thoughts like the ones described in the post are not thoughts people actively engage their minds with; often they are not. Rather, they are somehow perhaps best perceived of as part of the OS. The convenient narratives are part of us and there’s no way to get rid of them. But thinking about them every now and then can’t hurt.
“External ballistics is the part of the science of ballistics that deals with the behaviour of a non-powered projectile in flight. External ballistics is frequently associated with firearms, and deals with the behaviour of the bullet after it exits the barrel and before it hits the target.”
“The main Soviet censorship body, Glavlit, employed 70,000 full-time staff not only to eliminate any undesirable printed materials, but also “to ensure that the correct ideological spin was put on every published item”.”
And Glavlit wasn’t even the only censorship body in the Soviet Union. Also:
“CIA estimated in 1980s that the budget of Soviet propaganda abroad was between 3.5-4.0 billion dollars.” […] “Propaganda abroad was partly conducted by Soviet intelligence agencies. GRU alone spent more than $1 billion for propaganda and peace movements against Vietnam War”
3. Concussion (this is a ‘good article’).
4. Crypsis. “In ecology, crypsis is the ability of an organism to avoid observation or detection by other organisms. It may be either a predation strategy or an antipredator adaptation, and methods include camouflage, nocturnality, subterranean lifestyle, transparency, and mimicry.”
The article has this awesome image (click to view in higher res.):
The frog you’re looking for is just to the left of the top end of the vertical stick. Can you see it? I couldn’t. Go here for an image up close where you can see the frog highlighted.
“The Ascomycota are a Division/Phylum of the kingdom Fungi, and subkingdom Dikarya. Its members are commonly known as the Sac fungi. They are the largest phylum of Fungi, with over 64,000 species. The defining feature of this fungal group is the “ascus” (from Greek: ἀσκός (askos), meaning “sac” or “wineskin”), a microscopic sexual structure in which nonmotile spores, called ascospores, are formed. […]
The ascomycetes are a monophyletic group, i.e., all of its members trace back to one common ancestor. This group is of particular relevance to humans as sources for medicinally important compounds, such as antibiotics and for making bread, alcoholic beverages, and cheese, but also as pathogens of humans and plants. Familiar examples of sac fungi include morels, truffles, brewer’s yeast and baker’s yeast, Dead Man’s Fingers, and cup fungi. The fungal symbionts in the majority of lichens (loosely termed “ascolichens”) such as Cladonia belong to the Ascomycota. There are many plant-pathogenic ascomycetes, including apple scab, rice blast, the ergot fungi, black knot, and the powdery mildews. Several species of ascomycetes are biological model organisms in laboratory research. Most famously Neurospora crassa, several species of yeasts, and Aspergillus species are used in many genetics and cell biology studies. Penicillium species on cheeses and those producing antibiotics for treating bacterial infectious diseases are examples of taxa that belong to the Ascomycota.”
The article has lots of additional links if you want to know more.
6. Cameroon. (this is a featured article)
From the European Public Choice Society’s meeting this year. There’s a lot more stuff here.
Last I was home I found out that the idea that managers might decide to deliberately ‘boost their numbers’ in various ways strategically some time before leaving for another job was something my parents had never even considered. I find it obvious that politicians from time to time decide to employ similar strategies by trying to make the important numbers look good up to the election and then take the hit a year or two later, once they’re in office.
3. Econometric Estimates of Deterrence of the Death Penalty: Facts or Ideology? From the concluding remarks:
“Considering all these results, a critical and cautious examination of them leads to the conviction that we cannot draw any strong conclusion: while there is some evidence that a deterrent effect might exist, it is too fragile to be sure about it and the possible quantitative effect usually measured by the number of homicides prevented by each execution is so uncertain that it is difficult to conclude anything that would be relevant for policy purposes.”
4. Beneﬁt Morale and Cross-Country Diversity in Sick Pay Insurance. From the abstract:
“We analyze the impact of beneﬁt morale on sick pay entitlement levels in a political economy framework. Stronger beneﬁt morale reduces the number of recipients. On one hand this reduces the probability of receiving beneﬁts, on the other hand it makes insurance cheaper. Numerical simulations show that the probability eﬀect can dominate the price eﬀect and hence beneﬁt morale might decrease insurance levels.”
The ‘benefit morale’ mentioned is a social norm against beneﬁt fraud, so that you don’t claim benefits if you’re not sick. And yeah, I know I’ve linked to it before but I should probably leave a link to this every time I publish a post like this with multiple studies.
Some bits from the first chapter of the Phd Thesis by Malene Lamb.
“75% of the males in the sample work full-time, whereas only 54% of the women are employed full-time.”
“Finally, we have information about contributions to both labor market pension schemes and private pension schemes. […] The variables show how much the individual has contributed to the different schemes each year making it a good indicator for how much the individual has put aside to supplement the public retirement schemes. […] Around 95% of the individuals in our sample have made no contributions within a given year to a labor market pension schemes independently of which of the two types we consider. […] For private schemes the picture looks slightly better since ‘only’ 70% have no private capital pension and 75% have no private annuity pension.”
“If the spouse is working full-time it lowers the probability for the individual to enter early retirement. However, this effect only holds for women indicating that women actively participating in the labor market have a lower retirement hazard if their husband works full time. […] A longer spell of illness of the spouse significantly increases the retirement hazard indicating that people may leave the labor market earlier in order to take care of their spouse. Looking at the two sub-samples this effect is only significant for the men. […] In this context it is important to note that free medical care is available to everyone thus not forcing one member of the household to continue working in order to maintain a health insurance.”
“We have […] shown that the husbands’ characteristics do affect the retirement behaviour of their wives differently than the wives’ characteristics affect their husbands. Within all the variable groups (labor market, education, age, occupation, sector, financial indicator, and pension) included in the model we find that spousal differences exists. However we never find opposite significant spousal effects, it is always the case that it is only significant for one of them.
Women’s retirement hazard is affected positively by the husband’s experience, if the husband has a short education compared to basic education, the husband’s high contributions to a labor market capital pension scheme and finally medium or high contributions to a private annuity pension scheme. On the other hand women’s retirement hazard is affected negatively (thus retire later) if the husband works full time, is self-employed or works in construction compared to the public sector. Men’s retirement hazard is affected positively by the wife’s age, labor market pension payments or if she receives sickness benefits. Men retire later if the wife has been unemployed, is high educated, not working as a high-salaried worker, is working in the construction, trade or transport sector compared to the public sector. Overall, we find more significant effects for men indicating that they are more influenced by their spouse in the early retirement decision compared to women. This corresponds to the results found in Gustman and Steinmeier (2000) and Coile (2004).”
Most of this I didn’t know. The sample is based on all Danish workers who were active in the labor market at the age of 50 in 1985 (99.498 individuals) – so many of the results probably don’t hold for the whole population (/entire workforce, all Danes/…). For instance private savings and the level of education are both variables likely to be somewhat higher in the younger cohorts. It seems that a majority in the cohort they looked at didn’t consider it to be necessary to save any money for retirement at all – I was simply flabbergasted when I read those numbers. Though it is worth remembering the role real estate plays in the savings equation (/and of course also the impact of the public pension scheme); in a way it makes more sense for a Dane to implicitly put the savings into the house than it does for an American, as the median Dane will never get into a situation where he or she suddenly needs to raise a lot of money fast to pay for a medical procedure – the liquidity part is much less important.
Radiation Dose-Response Relationships for Thyroid Nodules and Autoimmune Thyroid Diseases in Hiroshima and Nagasaki Atomic Bomb Survivors
Here’s the link. The easiest way to read this study is to save the pdf and open it in a pdf-reader like Adobe or Foxit – it looks quite messy the way it’s set up on that page. They’ve analyzed the data of more than 4000 survivors of the bombings more than 50 years after the bombings – in itself an amazing feat. The main findings:
“Results: Thyroid diseases were identified in 1833 (44.8%) of the total participants (436 men [32.2% of men] and 1397 women [51.0% of women]) (P<.001). In 3185 participants, excluding persons exposed in utero, not in the city at the time of the atomic bombings, or with unknown radiation dose, the prevalence of all solid nodules, malignant tumors, benign nodules, and cysts was 14.6%, 2.2%, 4.9%, and 7.7%, respectively. The prevalence of positive thyroid antibodies, antithyroid antibody–positive hypothyroidism, and Graves disease was 28.2%, 3.2%, and 1.2%, respectively. A significant linear dose-response relationship was observed for the prevalence of all solid nodules, malignant tumors, benign nodules, and cysts (P<.001). We estimate that about 28% of all solid nodules, 37% of malignant tumors, 31% of benign nodules, and 25% of cysts are associated with radiation exposure at a mean and median thyroid radiation dose of 0.449 Sv and 0.087 Sv, respectively. No significant dose-response relationship was observed for positive antithyroid antibodies (P=.20), antithyroid antibody–positive hypothyroidism (P=.92), or Graves disease (P=.10).
Conclusions: A significant linear radiation dose response for thyroid nodules, including malignant tumors and benign nodules, exists in atomic bomb survivors. However, there is no significant dose response for autoimmune thyroid diseases."
Basically, the study says that almost half, 45%, of all the atomic bomb survivors from Hiroshima and Nagasaki who're still alive have some sort of thyroid disease. One of the things that surprised me when reading this study is that the lower the age of exposure, the higher the risk of developing malignancies later on. It makes perfect sense, I just hadn’t thought about that. The excess odds ratio pr. Sievert of developing solid nodules was almost four times as high among those exposed at the age of 0-9 than among those exposed at the age of 10-19. As an aside, when Chernobyl blew up I was less than one year old.
And now for something completely different (target group: Danish readers). Here are the titles of the top posts on the front page of the main Danish wordpress site right now:
1. Bla. om at have de forkerte forbilleder og at gøre krav på sin lykke.
2. Færdig med at tørre røv
3. “Du kommer ingen vegne med at have det nemt”
4. Køkkenombygning – vejs ende. Næsten
6. Der er hylder der skal findes
If a pregnant female wants to increase her likelihood of having grandchildren down the road, she might be well-advised to stay away from painkillers during her pregnancy. Link.
I’ll be very busy during the next week, so don’t expect many updates here and don’t get angry if I don’t respond to your comments. The above link was a link I’d saved for a day like today, where I don’t have the energy to blog but ought to do it anyway in order to keep the blog alive. I don’t have many more of those links lying around, maybe I should have saved it another day or two, but now I’ve already posted it, so.. In a week or so, I’ll try to get back on track.
2. Dung beetle.
“Dung beetles are beetles that feed partly or exclusively on feces. All of these species belong to the superfamily Scarabaeoidea; most of them to the subfamilies Scarabaeinae and Aphodiinae of the family Scarabaeidae. This beetle can also be referred to as the scarab beetle. As most species of Scarabaeinae feed exclusively on feces, that subfamily is often dubbed true dung beetles. There are dung-feeding beetles which belong to other families, such as the Geotrupidae (the earth-boring dung beetle). The Scarabaeinae alone comprises more than 5,000 species.”
“Dung beetles can roll up to 50 times their weight.” Those animals are awesome!
3. Well, they had me fooled. Imagine being the curious Chinese 15-year-old who finds that page in a google search. Imagine that you have poor English skills, have no knowledge of what The Onion is and have very little knowledge about Ancient Greece.
4. Comparison of Weight-Loss Diets with Different Compositions of Fat, Protein, and Carbohydrates. Exactly what it says on the tin. Haven’t read the study yet, but it looks interesting. Here are some highlights:
“We randomly assigned 811 overweight adults to one of four diets; the targeted percentages of energy derived from fat, protein, and carbohydrates in the four diets were 20, 15, and 65%; 20, 25, and 55%; 40, 15, and 45%; and 40, 25, and 35%. The diets consisted of similar foods and met guidelines for cardiovascular health. The participants were offered group and individual instructional sessions for 2 years. […]
At 6 months, participants assigned to each diet had lost an average of 6 kg, which represented 7% of their initial weight; they began to regain weight after 12 months. By 2 years, weight loss remained similar in those who were assigned to a diet with 15% protein and those assigned to a diet with 25% protein (3.0 and 3.6 kg, respectively); in those assigned to a diet with 20% fat and those assigned to a diet with 40% fat (3.3 kg for both groups); and in those assigned to a diet with 65% carbohydrates and those assigned to a diet with 35% carbohydrates (2.9 and 3.4 kg, respectively) (P>0.20 for all comparisons). Among the 80% of participants who completed the trial, the average weight loss was 4 kg; 14 to 15% of the participants had a reduction of at least 10% of their initial body weight. Satiety, hunger, satisfaction with the diet, and attendance at group sessions were similar for all diets; attendance was strongly associated with weight loss (0.2 kg per session attended). The diets improved lipid-related risk factors and fasting insulin levels.
Reduced-calorie diets result in clinically meaningful weight loss regardless of which macronutrients they emphasize.” [my emphasis]
The title of the paper, Inequalities in healthy life years in the 25 countries of the European Union in 2005: a cross-national meta-regression analysis, was too long for me to use as a post title.
“Background: Although life expectancy in the European Union (EU) is increasing, whether most of these extra years are spent in good health is unclear. This information would be crucial to both contain health-care costs and increase labour-force participation for older people. We investigated inequalities in life expectancies and healthy life years (HLYs) at 50 years of age for the 25 countries in the EU in 2005 and the potential for increasing the proportion of older people in the labour force.”
“Findings: In 2005, an average 50-year-old man in the 25 EU countries could expect to live until 67,3 years free of activity limitation, and a woman to 68,1 years. HLYs at 50 years for both men and women varied more between countries than did life expectancy (HLY range for men: from 9,1 years in Estonia to 23,6 years in Denmark; for women: from 10,4 years in Estonia to 24,1 years in Denmark). Gross domestic product and expenditure on elderly care were both positively associated with HLYs at 50 years in men and women (p<0,039 for both indicators and sexes); however, in men alone, long-term unemployment was negatively associated (p=0,023) and life-long learning positively associated (p=0,021) with HLYs at 50 years of age."
I did not know that Denmark did that well on this metric. The link has a lot more.
I had no idea it was that bad. Here’s the link.
“Measured average height, weight, and waist circumference for adults ages 20 years and over
Height (inches): 69.4 (176,3 cm)
Weight (pounds): 194.7 (88,5 kg)
Waist circumference (inches): 39.7 (100,8 cm)
Height (inches): 63.8 (162,1 cm)
Weight (pounds): 164.7 (74,9 kg)
Waist circumference (inches): 37.0 (94 cm)”
The numbers are from 2003-2006, and I’m pretty sure they haven’t gone down during the time that has passed. In case you were wondering, I’m at about 73-74 kg most of the time, so there’s not much of a difference. But still!
Danish females weighed an average of 68,0 kg in 2005, whereas the male average was 83,1 kg (the link has a lot more). The Danish females gained 5,8 kg’s on average from 1987 to 2005, and if that trend has continued since then, they are at 69,6 kg now – not that far behind.
Yes, I know there are significant regional differences in the US, for more on that aspect you can go here.
No, that’s not actually what the study says but I’m sure that’s what the headlines will sound like when the journalists get their hands on this study…
“Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period.”
“social relationships were more predictive of the risk of death in studies that considered complex measurements of social integration than in studies that considered simple evaluations such as marital status.”
Here’s a link to the study. The estimated effects of social relationsships on mortality are, in case you were in doubt, huge:
“These findings indicate that the influence of social relationships on the risk of death are comparable with well-established risk factors for mortality such as smoking and alcohol consumption and exceed the influence of other risk factors such as physical inactivity and obesity. Furthermore, the overall effect of social relationships on mortality reported in this meta-analysis might be an underestimate, because many of the studies used simple single-item measures of social isolation rather than a complex measurement.”
With respect to diabetes, it’s now understood that several types of cancer are more common: colon, pancreas, and breast.
Link, the main topic of the article is the hypothesized link between injections of insulin analogs and cancer.
My granddad on my father’s side died of colon cancer, so that one already runs in the family. This link has some information about the genetics of that disease.
From the comment section of this post published on Pharyngula, a new blog William Jansen introduced me to recently (thanks for that!). It’s a comment responding to another comment mentioning the meme that if you can’t do anything about it, pretend it’s a good thing :
“People do this with all kinds of diseases and disabilities — look at the number of people who think that being blind must automagically make you able to hear like a dog, or the sheerly annoying (as a person with a disability) number of people who seem to think that disabled (and sick) people exist to be moral exemplars to them.
I blame the ancient Greeks, personally; there’s no character in a ancient Greek work of literature who has what we’d now call a disease or disability who isn’t “gifted” or otherwise special in some way (the blind or lame prophet, for example), and the trope has persisted through western literature so universally and for so long now, people have basically been subconsciously conditioned from birth to believe that disease, disability, and infirmity must always come with some kind of (hidden) upside. Add that to the human tendency to construct narrative out of temporally-connected series of events, and everyone is looking for a good story in adversity.
The reality is, disease and disability aren’t morally uplifting and don’t exist to teach other people how to be patient, tolerant, or any of that other BS. They’re ugly, usually painful, inconvenient, and undignified, and, above all, not about anyone but the person who has them (and maybe their immediate circle).”
It’s a small minority that do not think of aging this way too; as something that has its costs and its benefits. I, on the other hand, like to think of aging as just another incurable, complex disease (or …set of diseases…) that’s slowly killing all of us.