Research Blogging - Anthropology - English

An Aboriginal Australian genome reveals separate human dispersals into Asia

2012-05-25T03:04:32Z

This blog section concerns a trendy debate in science, the human population history, which has extensions into daily life, as it can constitutes a topic of general public curiosity. Therefore, let’s see what is contribution described herein.BackgroundModern human populations seems to be derived from a single African ancestral population, under the well supported “out of Africa” hypothesis (1). Particularly, for eastern Asian colonization a “single-dispersal” model have been hypothesized (2), which suggest the aboriginal australians are a lineage diversified recently within the Asian cluster. This hypothesis could be summarized in a topological representation, as drawn in figure 1A of the article (Africans,(Europeans,(Asians,Australians))). Recent studies dated the split between Europeans and Asians around 17K-43K years before the present (ybp). In addition, archaeological evidence supports modern humans in Australia back to ~50K ybp. Those inferences are incompatible with the above mentioned hypothesis, at least in a time framework. A second scenario could be hypothesized, with an early branching process and occupation of Australia, and probable later genetic exchange between Asians and Australians, described as (Africans, (Australians,(Asians, Europeans)). This possibility has been non tested so far. Using an ancient, free of current admixtures, aboriginal australian genome, and SNPs data from different human populations, as well as, a background in molecular evolution and population genetic theories, this paper aims to distinguish between competing hypotheses to tackle the human population relatedness and migrations history of ancient australian populations.The facts in briefA 100-year-old lock of hair from an aboriginal Australian male (from Museum of Archaeology and Ethnology, UK)31 Institutions implied in a worldwide scale58 Authors, with same geographical extentAn ancient genome sequenced by Illumina technology and SNP-chip on other human populationsComputational analyses (PCA, clustering methods, ABBA/BABA expectations)A Science podcast interview (http://www.sciencemag.org/content/334/6052/94/suppl/DC2)Discussion We found the paper quite convincing in testing the two possible scenarios for human colonization in the Australian area. Next paragraphs will describe and discuss the evidence and test they used.1. Testing the genetic clustering of Aboriginal Australian genome.The principal component analysis illustrated in figure 1B shows the clustering pattern from 1220 individuals SNP chip data (449k SNPs), covering 79 human populations. This figure revealed a close relationship between the Australian genome, Highland Papua New Guinea (PNG), Bougainville and Aeta samples, all of them from the australo-melanesian region. That pattern could exclude any European contamination of the sample, which is highly probable by his long handling by Europeans. We noted the geographical tendency of a “continuous” colonization for human populations outside of Africa. I quoted continuous to clarify we are not referring to a single wave of colonization, but to a geographical ordination of the populations. A confusing point was expressed for the PCA inset, which looks like a 3D-box, but it already corresponds just to a zoom-in on the same PCA graph. A further review of the next PCA axes on supplementary material evidenced a very clear differentiation of the australo-melanesian sequences in the axis4.We speculated about the amount of data explained in the first two PCA axes, which is not described. Contrary to our expectations, from experiences in other types of characters (as morphology and climatic variables), the proportion of variance explained on this plot seems to be very low, as usual for genomic studies. Then, we discussed a bit the idea of a checklist of requirements when a publication is being prepared: if you are planning to present an analysis, take at hand i, ii, iii and please do not forget to include them.2. Testing admixture between Aboriginal Australian genome and other populationsThe figure 1C describes the ancestry proportions of all individuals SNPs set, obtained by a maximum likelihood estimation in Admixture software. This clustering analysis resembles the Structure k-categories approach, in which each line in the plot correspond to an individual and the colors represent the ancestral populations identities. The number of k-categories is assigned a-priori, and can modify the ancestry proportions of certain individuals revealing admixture processes between populations. At first, using a k=5, the aboriginal australian sample appears belonging to the same ancestral population than PNG and a higher proportion of the Bougainville individuals. Interestingly, south Asian population seems to share a small proportion of the SNPs with the ancestral aboriginal australian category. Once we moved in deep k-values, as far as k=20, the aboriginal australian genome appears more mixed with PNG, Bougainville, Aetas and South Asian populations.We debated the accuracy of use an individual genome to represent the admixture in the ancestral aboriginal australian population, and the unknown variability of the population at the ancient time, which is not being considered here. We formulated how could be affected the admixture patterns if this aboriginal Australian genome represents the most or the least mixed individual in the ancestral population? We wondered why there are not other recent Australian samples? Even if current aborigines inhabit in Australia. At this point in the discussion, we moved into more socio-political issues about the use of samples and information, as I stated at the beginning, this topic could be of general concern and discussion for several reasons.The evidence presented so far and an additional test below can help to distinguish between single vs. multiple dispersals “out of Africa” and likely the proportion of admixture between the first established populations and the second wave of migration. Furthermore, questions about how or why the second migration replaced almost in a complete way the first one, from my point of view, constitute statements largely "historical" and therefore difficult to draw and test from the evidence available. I consider is very difficult to go beyond of the patterns and processes we are able to model and test.3. D-test and ABBA/BABA hypothesis We tried to identify the goal and configuration of this test to discriminate between the competing hypotheses. Complete information of the test could be found in references 3 and 4. I will try to summarize it in a nutshell. The D-test is a four-taxon configuration (see figure) in which only biallelic sites are considered (A and B variants), two out of four taxa have fixed states, commonly on the outgroup sequence (here the Africans, but also the Europeans), and the other two sites differ between groups (here Aboriginals and Asians). This configuration produces either BABA or ABBA patterns. The next step is to count the number of sites supporting one or other patterns. The D test = ∑ (sites ABBA - sites BABA) / ∑ total sites. Usually, the test was defined to identify admixture between populations (with AB/BA sites), with the expectation of an equal number of the two types of sites. D test can be considered more robust to sequencing errors because it compares nucleotides in more than one sequence, which is less probable that have been taken place twice by error. The authors explicitly said the test do not allow to distinguish neither between the two models of origin, nor gene flow between Asians and Australian populations, however I consider the D-test performed here can support the multiple dispersal model, due to a statistically significant excess of sites grouping Africans and Australian Aboriginal genomes (sites with pattern 2 in figure). Expected vs. observed values of the D-test can facilitate the hypotheses discrimination (as they tried on the Table 2), however the expected values reported here for single and multiple dispersal models are so closer each other (~50%), with no credible intervals, that does difficult to support one or other hypothesis with the observed patterns. Finally, it is worthy of attention in the implementation of the D-test, consider that the patterns on current populations given the hypothetical past events, may have been altered by many other evolutionary processes as secondary gene flow, structure in the ancient population, incomplete lineage sorting, among others.Figure 1. Grouping site patterns 1 and 2 used in D-test. Note that African and European populations have fixed states, whereas that Aboriginal Australian and Asian populations vary. This figure is a modification of the figure 3 in reference 5. Even though it is not clear the ABBA/BABA patters, the different grouping patterns are based on the article text describing the two models of early dispersal hypotheses used to perform the test....

Rasmussen, M., Guo, X., Wang, Y., Lohmueller, K., Rasmussen, S., Albrechtsen, A., Skotte, L., Lindgreen, S., Metspalu, M., Jombart, T.... (2011) An Aboriginal Australian Genome Reveals Separate Human Dispersals into Asia. Science, 334(6052), 94-98. DOI: 10.1126/science.1211177

Is the influence of classic writers on modern ones diminishing?

2012-05-23T17:50:00Z

Late last year, some researchers in the U.S. conducted a study that tried to determine the changing literary influences on writers, and the story seemed to be making the rounds on the news last week. The essential thesis is this: the influence of classic writers on our contemporaries is not what it used to be. Put in those terms, it sounds rather condemning, as though today’s writers are not reading up on their Chaucer and Milton and so are less culturally informed. That’s certainly how it’s been reported, but what did the researchers really mean? And is the claim even true? The paper’s basic purpose was to conduct the first large-scale stylometric analysis of literature throughout different periods (i.e. an analysis of different writers’ linguistic styles), which they achieved thanks to the marvellous resources of Project Gutenberg. The most important facet of the study, with the greatest ramifications on the conclusions we can draw from it, is that they focused on content-free words, which they defined as: “the ‘syntactic glue’ of a language: they are words that carry little meaning on their own but form the bridge between words that convey meaning.” Such words include and, but, to, and of. They narrowed their analysis to 537 authors, all of whom had at least 5 works on Project Gutenberg, though given the copyright laws that govern the texts they’re allowed to archive, they ranged from 1550-1952. Through some fancy linguistic equations and mathematical analysis, they were able to determine that the stylistic influences of preceding writers on their successors has diminished considerably in recent times. However, it’s extremely important to recognise that this concerns stylistic influence - the ands, buts, and ofs that a writer uses. This is how we can estimate the historical position of a line of Joyce and a line of Shakespeare without knowing exactly who we’re reading. It has little to do with the content of their works - their ideas, stories, and arguments - which bear no relation to their sentence structures. It’s quite misleading to even call the effects on style an “influence”, as a writer’s idiosyncratic use of prepositions and conjunctions is more likely a product of the natural evolution of language, driven by many complex social factors, than by the books they read. Of course, their analysis presented a continuous range of texts spanning 400 years, but to make a statement about anything “modern”, it’s necessary to determine an arbitrary boundary between that and “old” texts. While you or I might intuitively draw this line around 1900, the authors explicitly stated their “modern” writers as extending from 1784, so the results cannot be said to demonstrate an effect that is unique to the writers of today and yesterday - this goes right back to the end of the 18th century. They did go on to make further subdivisions, but this graph from their article demonstrates a paucity of data in some areas despite the number of books they covered: Here we see that the vast majority of analysis was concentrated on works from around 1830-1930. There were far fewer works from the decades straddling either side of that period, and an extremely small amount from before 1750. So what exactly can we learn from this paper? Not much. They’re right to suggest that it provides a statistical basis for the common perception that there exist “literary styles of the time”, but these regard linguistic style, not ideological influence or familiarity with classic literature. Our contemporary writers are perfectly able to read as much classic fiction as their forebears while demonstrating smaller amounts of linguistic influence. The reasons for the diminished effect are also inconclusive - while it is most strongly implied that it has to do with reading habits and aesthetic movements, it’s conceivable that the effects of linguistic influence, particularly in English, have been greatly affected by globalisation - a factor not taken into account. So don’t worry, the writers of today are not necessarily ignorant of their cultural heritage, it’s just journalists once again making tangential, unsubstantiated assumptions about a research article that the researchers gave them no cause for making. ————— Hughes JM, Foti NJ, Krakauer DC, & Rockmore DN (2012). ‘Quantitative patterns of stylistic influence in the evolution of literature’ Proceedings of the National Academy of Sciences of the United States of America, 109 (20), 7682-6 PMID: 22547796...

Hughes JM, Foti NJ, Krakauer DC, & Rockmore DN. (2012) 'Quantitative patterns of stylistic influence in the evolution of literature'. Proceedings of the National Academy of Sciences of the United States of America, 109(20), 7682-6. PMID: 22547796

Rich People May Not Be So Unethical

2012-05-23T14:47:31Z

There was quite the stir a few weeks back about a psychology paper claiming that rich people aren't very nice: Higher social class predicts increased unethical behavior. The article, in PNAS, reported that upper class individuals were more likely to lie, cheat, and break traffic laws.However, these results have been branded "unbelievable" in a Letter to PNAS just published. Psychologist Gregory Francis notes that the paper contains the results of 7 seperate experiments, and they all found statistically significiant socioeconomic effects on unethical behaviour.Those 7 replications of the effect "might appear to provide strong evidence for the claim" - one study good, 7 studies better, right? - but Francis says that actually, it's too good to be believed.Each of the studies was fairly small, and the effects they found were modest, and only just significant. So the observed power of the studies - the probability that a study of that size would detect the effect that they did, in fact, find - was only about 50-88% in each case.Think of it this way: if you took a pack of cards and discarded half of the black ones, then shuffled the remainder, a random card from the deck would most likely be red. But even so, it would still be very unlikely that you'd pick 10 reds in a row.The chances of all 7 studies finding a positive result - even assuming that the effect claimed in the paper was real - is just 2%, by Francis's calculations.Ow.He concludes "The low probability of the experimental findings suggests that the data are contaminated with publication bias. Piff et al. may have (perhaps unwittingly) run, but not reported, additional experiments that failed to reject the null hypothesis (the file drawer problem), or they may have run the experiments in a way that improperly increased the rejection rate of the null hypothesis (4)".What might have happened? Maybe there were more than 7 studies and... maybe they peeked at the data before deciding on the same size, took other outcome measures unreported. See also the 9 Circles of Scientific Hell.Piff et al respond, firmly denying that they ran any other unpublished experiments, and saying that they "scrutinized our data collection procedures, coding protocols, experimental methods, and debriefing responses. In no case have we found anything untoward." They go on to criticize the method Francis used to get his magic 2% figure, which they point out relies on some debatable assumptions.Even if you buy the 2% figure, it doesn't mean that the true effect is zero; it might be real, but exaggerated. Ultimately it all becomes rather murky and subjective, which is why I think we need preregistration of research, which would prevent any possibility of such data fiddling, and also remove the possibility of false accusations of it... but that's another story.Francis, G. (2012). Evidence that publication bias contaminated studies relating social class and unethical behavior Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1203591109...

Francis, G. (2012) Evidence that publication bias contaminated studies relating social class and unethical behavior. Proceedings of the National Academy of Sciences. DOI: 10.1073/pnas.1203591109

Gaydar Works (A Bit, On Facebook)

2012-05-22T14:28:31Z

The media are gleefully reporting a recent paper showing that "gaydar is real" - we can tell who's gay just by looking: The Roles of Featural and Configural Face Processing in Snap Judgments of Sexual OrientationWhile it's a fine paper, I'm afraid that the results really aren't that exciting.American undergraduate students were able to classify people as gay or straight with better than chance accuracy, based purely on photos of their face. For male photos, the hit rate was 0.57; for women it was better with an accuracy of 0.65.However, that's on a scale where you get 0.50 by flipping a coin. So saying that gaydar is '65% accurate', as almost everyone has, is misleading. Still, the numbers seem solid. The sample sizes were large and the effect was replicated very convincingly in two experiments.However... this tells us very little about real world "gaydar", and it wasn't intended to. There are reasons to think it could underestimate the accuracy:Most importantly - people only saw the pictures for 50 milliseconds each. 1/20th of a second. Followed by a backward mask. That's right on the threshold of conscious perception, almost 'subliminal' but not quite. With longer viewing times, they might have done better.All the faces were black and white photos with the hair and ears cropped out (see above - and I think those two photos from the paper are the authors, although I may be wrong!). Anyone with facial hair, glasses, or any other 'accessories' wasn't used. In the real world, we have that extra information.In real life, we get clues from facial expressions, body language, voice, clothes. You could argue that these are being used (consciously or not) specifically as signals of sexuality, so they don't count as 'gaydar' - but more on that later. But it could also overestimate gaydar's powers:These were photos that people chose for their Facebook profiles. We all know how much effort some people put into that choice. We also know that different photos of the same person can often seem like two different people. Your Facebook pic is probably the most "selected" photo of you in existence. It would be better - but also much harder - to use passport photos.All of the gays in the study were out of the closet: they broadcast their sexuality on Facebook. But lots of gay people don't do that. Now those cases are probably where 'gaydar' is most likely to be of interest to most people, I think; those people might be harder to spot.As far as I can tell, this study wasn't intended to "prove that gaydar works". It was meant to examine how it works, by seeing whether it works very quickly (yes - in 50 ms in some cases). The authors also tested how accuracy was changed by flipping the photos upside down; this reduced accuracy but it was still well above chance. Ultimately, we need to ask what "gaydar" means and why we find it so interesting.On a superficial level, it just means being able to sense, from someone's appearance, if they're gay. That certainly does 'work' - if you see a guy coming out of a gay club in a tight pink Boy George t-shirt then yeah, he's probably gay. But he's (effectively) told you so, by being in that club and wearing those clothes, so that's not very interesting. That's an extreme case, but clearly people advertise their sexuality (and much else of course) all the time. Gaydar, in a weak sense, is just perception.I think what makes "gaydar" intriguing is the stronger idea that it can go beneath such adverts. That we can see who's really gay, whether or not they admit it, even to themselves. If that were possible, then it would seem to mean that homosexuality is part of the essence of some people - in other words, that it's a biological trait.So gaydar in a strong sense is risque. It calls to mind un-PC ideas such as physiognomy and would seem to validate various stereotypes which are the stuff of dirty jokes more than polite discussion.Does gaydar in this strong, exciting sense exist? That's another question. This study doesn't tell us.Tabak, J., and Zayas, V. (2012). The Roles of Featural and Configural Face Processing in Snap Judgments of Sexual Orientation PLoS ONE, 7 (5) DOI: 10.1371/journal.pone.0036671...

Tabak, J., & Zayas, V. (2012) The Roles of Featural and Configural Face Processing in Snap Judgments of Sexual Orientation. PLoS ONE, 7(5). DOI: 10.1371/journal.pone.0036671

Let the Buyer Beware

2012-05-22T13:26:00Z

"Modern societies are complex systems" may be the understatement of the year. Obvious or not, however, it must be stated when attempting to model even some minuscule aspect of such a society. Take, for instance......

Tiago P. Peixoto, & Stefan Bornholdt. (2012) No Need for Conspiracy: Self-Organized Cartel Formation in a Modified Trust Game. Physical Review Letters, 108(21), 218702. info:/10.1103/PhysRevLett.108.218702

Using Mortuary Evidence to Determine Political Economy

2012-05-22T10:43:35Z

Political economy refers to the social relations and political structures that guide the economic practices of a group. Traditionally this has meant looking at the coercion and control of the commoners by elites. However, newer interpretations include the role that the non-elites play in structuring these relations and shaping the economy, as well as the … Continue reading »...

Shepard, B. (2012) Political economic reorganization among non-state societies: A case study using Middle Holocene mortuary data from the Cis-Baikal, Russia. Journal of Anthropological Archaeology, 31(3), 365-380. DOI: 10.1016/j.jaa.2012.03.001

Linguistics and Archaeology in North America

2012-05-22T00:56:54Z

The same special issue of the journal World Archaeology that I was discussing in the previous post has an article looking specifically at the relationship between linguistic and archaeological evidence in the study of the prehistory of North America. It is by M. Dale Kinkade and J. V. Powell, two linguists who specialized in the languages [...]...

Kinkade, M., & Powell, J. (1976) Language and the prehistory of North America. World Archaeology, 8(1), 83-100. DOI: 10.1080/00438243.1976.9979654

What would you do?

2012-05-21T20:41:54Z

Caroline Tennant Kelly with two of her photos from the Cherbourg Aboriginal Settlement (Source: Sydney Morning Herald at http://www.smh.com.au/nsw/the-bohemian-and-her-mission-20100416-skgk.html) In 1924 the first university Department of Anthropology in Australia was founded at the University of Sydney. The founding professor was … Continue reading →...

Kidd, Rosalind. (1997) The Way We Civilise: Aboriginal Affairs - the untold story. University of Queensland Press. info:/

Having a Water Bottle for a Mom Not Ideal

2012-05-21T15:09:02Z

In the wild, young rhesus macaques can reasonably expect not to have their mothers replaced by kitchen props. The monkeys depend on their moms to nurse them and tote them through tree branches while they're small, just like other primates. But a laboratory experiment in Maryland took these babies from their mothers and had them raised alone or in groups of their peers. The monkeys' strange infancies had physical and mental effects that lasted into adulthood. At the National Institute of Child Health and Human Development (part of the National Institutes of Health), rhesus macaques born between 2002 and 2007 were randomly assigned to one of three groups. The lucky first group got to stay with their mothers, who kept their young close by while living in a large cage with other monkeys. The rest of the young monkeys were taken from their mothers and reared by humans in a nursery for their first five weeks of life. Then, if they were in the second experimental group, they were put into a cage with three other monkeys of the same age. The four peers were left to "raise" each other, Lord of the Flies style. The final group of monkeys, after being nursed by humans for five weeks, spent two hours a day in these same peer cages. During the remaining 22 hours, they lived alone in a cage with a "surrogate mother." The name is a bit of an insult to primate intelligence, though, since researchers describe this object as "effectively a terry cloth-covered hot water bottle hanging from the top of the cage." By the end of their first year of life, all the juvenile monkeys had been moved from their experimental cages into one social group. Now the researchers, led by Gabriella Conti at the University of Chicago, began to collect data on the monkeys' health. Over the years of the study, they watched 231 rhesus macaques grow up in this bizarre daycare system. Even though the monkeys all ended up living together, their disparate childhoods left a mark. The first clear effect was illness. Male monkeys that had been raised by a "surrogate" got sick nearly twice as often as mother-raised or peer-raised monkeys, even though by this time in their lives they all shared the same living conditions. Nearly every surrogate-raised male monkey had an illness at some point during the study. Female monkeys that had been raised by peers, rather than by a real or fake mother, were more likely to have wounds and bald patches once they were living in the large group. Since these females displayed more aggressive behavior, the researchers think they may have been starting fights with the other monkeys. Their aggression may have goaded other monkeys into biting them and pulling their hair out. And across all the groups taken away from their mothers—male and female, peer-raised and surrogate-raised—monkeys were more likely to have repetitive habits called stereotypies. In the zoo, a stereotypy such as pacing or swimming in circles suggests that an animal is in distress. In humans, stereotypies can be a symptom of autism. Habits displayed by the rhesus monkeys in this study included "digit sucking (the most frequent behavior), pacing, head tossing, self-grasping, saluting, spinning, rocking, circling, and swinging." Some of the difference between monkeys raised by their mothers and the rest could be due to breastfeeding, Conti points out. But the increased illness in male monkeys was limited to the surrogate-mom group; the peer-raised monkeys, despite also missing out on breastfeeding, didn't have extra illnesses. And although all motherless monkey groups showed an increase in stereotypy, the effect was greatest in surrogate-raised males. This suggests that even if formula feeding causes some of the health effects seen here, it can't account for all of them. The not-shocking conclusion is that monkeys need their moms to develop normally. Being raised parentless seems to make them less able to cope with infections or social stressors later in life. It's something to consider for research centers or zoos raising animals without their mothers. Even if the young have been orphaned or abandoned, there may be ways for human keepers to mitigate the damage. Conti is an economist, though, and she's more interested in another primate: humans. She compares the rhesus research to studies of human children raised without either of their parents. These studies have found mental and physical health effects in children in Romanian orphanages, for example, or Israeli kibbutzim (where kids were raised communally). As smart and independent as we are, we're still primates who need someone to haul us through the tree branches when we're young. Gabriella Conti, Christopher Hansman, James J. Heckman, Matthew F. X. Novak, Angela Ruggiero, & Stephen J. Suomi (2012). Primate evidence on the late health effects of early-life adversity PNAS : 10.1073/pnas.1205340109 Image: Baby Japanese macaque by Nemo's great uncle/Flickr...

Gabriella Conti, Christopher Hansman, James J. Heckman, Matthew F. X. Novak, Angela Ruggiero, & Stephen J. Suomi. (2012) Primate evidence on the late health effects of early-life adversity. PNAS. info:/10.1073/pnas.1205340109

Crossfit and the Search for the Perfect Diet: Aboriginal Australians and the Swiss

2012-05-20T11:41:00Z

Perusing Google News this morning I came across an article claiming that "Research Shows CrossFit Diet/Exercise Reduces Risk of Heart Disease". I clicked on that one immediately because, to the best of my knowledge, no scientific research has been published on relationships between high intensity CrossFit-type training and cardiovascular disease. If one were to do a search today on Web of Knowledge using the search term "Crossfit" you would get a single hit:Jansen, J., van Dam, N., Hoefsloot, H., & Smilde, A. (2009). Crossfit analysis: a novel method to characterize the dynamics of induced plant responses BMC Bioinformatics, 10 (1) DOI: 10.1186/1471-2105-10-425I'm sure the intentions of whoever wrote the press release were good . . . but . . . it is quite a stretch and I hope no one takes it seriously. Still, interesting that it made it into Google News. The research the author discusses has nothing to do with Crossfit. The press release does, however, attempt to associate a high-fat diet (promoted by some Crossfitters as healthy than other diets) with lower incidence of cardiovascular disease by comparing incidence of disease between residents of Switzerland and Australian aboriginals living in modern Australia. The claim was that a high-fat dining Swiss have less cardiovascular disease than the presumed low-fat dining Australian Aboriginals and that, therefore, high-fat diets are healthier than low-fat diets.I have not looked up the statistics for the Swiss, but Australian Aboriginals have been suffering increasing rates of cardiovascular disease over at least the last 30 years. Few modern Aboriginals are likely to be following a traditional Aboriginal diet. It is extremely unlikely that the increasing rate of heart disease observed in Australian Aboriginals has been caused by low intake of dietary fat. Aboriginals are suffering from increasing obesity and diabetes just like so much of the rest of the world. The high incidence of cardiovascular disease in Aboriginals may be due to genetic factors and a change to a Western-type diet but extremely unlikely to be caused by a low-fat diet (especially since they are not eating this way anymore anyway). There are also obviously many other differences between the Swiss and the Aboriginals (differences in poverty levels, availability of lederhosen and differences in other possibly important variables like intake of strong coffee and chocolate).This is all silly until one considers the disservice being done to readers who key into a health-related article's authoritative words (Research, World Health Organization, Medical, Clinical, Science) and believe the message makes sense. Rowley K, Walker KZ, Cohen J, Jenkins AJ, O'Neal D, Su Q, Best JD, & O'Dea K (2003). Inflammation and vascular endothelial activation in an Aboriginal population: relationships to coronary disease risk factors and nutritional markers. The Medical journal of Australia, 178 (10), 495-500 PMID: 12741936 O'Dea K (1991). Westernisation, insulin resistance and diabetes in Australian aborigines. The Medical journal of Australia, 155 (4), 258-64 PMID: 1875844...

Jansen, J., van Dam, N., Hoefsloot, H., & Smilde, A. (2009) Crossfit analysis: a novel method to characterize the dynamics of induced plant responses. BMC Bioinformatics, 10(1), 425. DOI: 10.1186/1471-2105-10-425

Rowley K, Walker KZ, Cohen J, Jenkins AJ, O'Neal D, Su Q, Best JD, & O'Dea K. (2003) Inflammation and vascular endothelial activation in an Aboriginal population: relationships to coronary disease risk factors and nutritional markers. The Medical journal of Australia, 178(10), 495-500. PMID: 12741936

O'Dea K. (1991) Westernisation, insulin resistance and diabetes in Australian aborigines. The Medical journal of Australia, 155(4), 258-64. PMID: 1875844