We introduce a diffusion index that quantifies whether research areas have been amplified within social and scientific bubbles, or have diffused and become evaluated more broadly. We illustrate the utility of our diffusion approach in tracking the trajectories of cardiac stem cell research (a bubble that collapsed) and cancer immunotherapy (which showed sustained growth).
Couldn’t we identify this stem cell bubble earlier? The authors believe that limited diffusion of biomedical knowledge anticipates abrupt decreases in popularity. But that takes time …
What’s again noticeable here, that in the stem cell research, the initial claim was later called into question leading to the retraction of more than 30 papers from claims of data fabrication.
Hopefully the thread here on “farming and allergy” is now coming to an end. I tried to refute it for many years – last attempt in 2020
the main objection against the farming hypothesis is the interpretation of a negative statistical association as a “protective” effect. Only after thorough exclusion of alternative explanations, this interpretation may be justified.
but unfortunately missed another paper from the literature that had already been published in 2011, sorry for that.
With environmental exposures aside, at least 2 profound differences between farming and nonfarming families could be a threat to the validity of such investigations. One of these is the long-term selection of traits and genes in favor of the demanding living conditions of farmers because the agricultural lifestyle is often handed down within families. Referring to the “healthy worker effect,” we could expect certain disadvantages to be underrepresented in a farming population, giving rise to the concept of a “healthy farmer effect.”
Also the second point of Grabenhenrich has never been assessed
The other area expected to be different when comparing farming and nonfarming families constitutes behavioral patterns, lifestyle, and knowledge. For example, “soft factors,” such as health care use, symptom perception, and labeling, as well as access to and interest in health-related information, are most likely to be distributed dissimilarly. This disparity, in turn, could severely affect the response pattern in studies basing their case definition mainly on questionnaires. A temporal shift of these soft factors toward increased cautiousness and awareness has been assumed to contribute to the worldwide increase in symptoms of allergic diseases and, to a lesser extent, to the increase in clinically apparent disease.10, 11 Why should such a change be uniform in all parts of a population? Particular subgroups might be susceptible to catch up more rapidly. This phenomenon could be studied by identifying outliers in otherwise homogenous populations.
in the hope that journalists and politicians will never find it?
True heroes in epidemiology and public health are Semmelweis, Snow, von Pettenkofer, Doll & Hill, Hesse & Rehn but not a MD who can not even explain an Odds Ratio…
So let’s have a more detailed look at farm parents. It can be drilled down to the question if parents are also “protected” or it is more likely that some affected parents just moved away. Here are 13 studies that included information about farm parents. Continue reading Parental allergy history at farms→
Here is the best explanation of a collider written by Julia Rohrer at www.the100.ci
Whenever X1 (conscientiousness) and X2 (intelligence) both cause Y (college attendance) in some manner, conditioning on Y will bias the relationship between X1 and X2 and potentially introduce a spurious association (or hide an existing link between X1 and X2, or exaggerate an existing link, or reverse the direction of the association…)
The cartoon makes it even clearer – confounder act on exposure and outcome, while collider condition on exposure and outcome.
Already in 2017 there was a Lancet paper with the super-long title “Effects of the Informed Health Choices primary school intervention on the ability of children in Uganda to assess the reliability of claims about treatment effects: a cluster-randomised controlled trial”. The paper is extensively discussed at vox.com
Andy Oxman is obsessed with the study of bullshit health claims and how to prevent them from spreading.
For decades, he’s been trying to find ways to get adults to think critically about the latest diet fads, vaccine rumors, or “miracle cures.” But he realized these efforts are often in vain: Adults can be stubborn old dogs — resistant to learning new things and changing their minds.
So not only Germany but also Uganda has its own bullshit hypothesis.
Asthma and atopy were inversely associated with presence of a farm within a radius of maximum 100m.
wich refers to their FIG 3
FIG 3 (click for zoom) Original legend: Number of farms within a given radius was dichotomized for at least one farm in the radius versus no farms. Associations are calculated by logistic regression resulting in odds ratios (OR) with 95%- confidence intervals.
The authors probably want to say that a non farm child that lives within a smaller distance to a farm shows a stronger negative association. Unfortunately it is not clear from the methods how the categories have been exactly defined, including or excluding category borders? And why is the highest category of 1.000-10.000 excluded here? There is a negative association with asthma in ALL strata irrespective of distance – what is the reference? The increased atopy risk by a farm in a circle with 1.000m radius is never discussed. BTW I am also quite sure that this plot has been produced with some kind of drawing software and not with “R version 3.2.3” if you zoom into the picture.
For whatever reason the authors abandon the distance definition above in favor of some data-derived classification afterwards. Why?
[1] children living on a farm currently run by the family [2] children not living on a farm, but with regular contact to farms, meaning at least once a week for a period of 6 months minimum and [3] children without any contact to farms.
I have no idea what regular contact is. But lets have a look on FIG 2
FIG 2: also misaligned and implausible Original legend: Distribution of environmental variables across exposure strata 1 = farm children, 2 = exposed non-farm children, 3 = non exposed non-farm children. Differences between the subgroups were statistically significant (p<0.01) except for ozone, altitude and distance to the next farm.
This is also not a facet_warp() as I would expect from a R analysis but some manually cut & pasted figures where P<0.01 is contradicting the methods. FIG 2.9 basically says that the distance to the next farm is not different in groups of “farm exposure”.
The abstract
The environmental variables greenness, tree cover, soil sealing, altitude, air pollution differed not only between farm and non-farm children, but also between farm children with and without another farm nearby.
is therefore wrong (it maybe even trivial as farms of course have less soil sealing than villages). In any case, we are now trapped in a loop as according to Fig 1 the prevalence of asthma and atopy over the exposure strata should have been different.
Keine Frage, die Lebensbedingungen auf Bauernhöfen sind anders. Mehr Tiere, mehr Dreck, mehr frische Luft, vieles ist anders als in der Großstadt. Dass es hier auch weniger Allergien gibt, wird wohl an den Bedingungen liegen, die bereits an einer der ersten Studien vor 30 Jahren zu sehen waren.
Clin Exp Allergy. 1999 Jan;29(1):28-34. https://doi.org/10.1016/S0140-6736(01)06252-3 Hier nicht relevante Daten ausgegraut
Auch die Eltern hatten schon weniger Allergien. Der “protektive” Effekt kann also einfach dadurch erklärt werden, dass mit weniger Eltern als “Risikofaktor” auch weniger Kinder Allergien haben. Und warum die Eltern wohl weniger Allergien haben? Nun ja, mit Heuschnupfen wird man nicht gern im Heu arbeiten wollen. Auch das zeigen Studien ziemlich eindeutig.
Wenn man genau hinschaut, dann haben alle Bauernhofstudien immer wieder dieselbe Argumentationsstruktur: weil die Bedingung X dort so ist, dann kann die Folge Y auch auf die Bedingung X zurückgeführt werden. Allerdings machen immer mehr Beschreibungen von X die Story nicht glaubwürdiger. Keine der jemals beschriebenen Bedingungen X, ist aus der Bauernhofsituation auf eine allgemeine Situation übertragbar gewesen, von einem einzigen verunglückten Versuch abgesehen.
Hier die Story mal erläutert an einem simulierten Datensatz – eine normal verteilte Allergiehäufigkeit und normal verteilte Endotoxinwerten. Zwischen beiden Variablen gibt es keine Korrelation.
Ausgangssituation: Jedes 10. Kind hat eine Allergie. Es gibt keine Korrelation zwischen Allergiehäufigkeit und Endotoxin.Wir beginnen nun eine Studie im ländlichen Raum (dunkelgrün) und sind dabei vor allem an den Bauernhöfen interessiert (hellgrün), also nur der Region mit hoher Endotoxinbelastung.Hier läuft aber schon seit längerem eine Wanderungsbewegung. Wer Heuschnupfen hat, wird nicht Heu machen können..Somit fallen in dem oberen rechten Quadranten Allergiker weg und verteilen sich im dunkelgrünen oder grauen Bereich. Müssen nicht viele sein, 30% weniger reichen schon.Wenn wir nun erneut eine Regressionsgleichung aufstellen, so gibt es eine negative Assoziation im ländlichen Bereich (kurze Linie) während in der Bevölkerung insgesamt die Verschiebung nicht besonders in das Gewicht fällt (lange Linie).
Das ist nun genau das Ergebnis der Bauernhofstudien.
Natürlich kann ein hoher Endotoxin Spiegel auf den Bauernhöfen eine bestimmte Wirkung haben – zumindest bei einigen Menschen und bei einigen Mäusen – aber mehr ist nach aktuellem Kenntnisstand auch sehr unwahrscheinlich.
Da die Lebensbedingungen auf dem Bauernhof angeblich protektiv sind, müsste es eigentlich Kinder geben, die eine Allergie haben sollten (zB wenn beide Eltern allergisch sind) aber nun doch keine Allergien bekommen haben. Solche Kinder gibt es aber nicht…
Third, in PARSIFAL dust from children’s mattresses were collected by vacuuming — it is not very likely that many helminthic eggs were transported from stable to bedroom. In GABRIELA, only airborne dust samples were collected which again may miss helminth eggs although being certainly present in stable dust.
Fourth, more microbial exposure and more fungal taxa on farms are a trivial finding.
The inverse associations of the diversity scores with asthma were not confounded by status with respect to living on a farm because adjustment did not change the respective point estimates for asthma (Table 2), although the associations became nonsignificant.
Small sample size, borderline p-values even after a long fishing expedition?
What do these strange “probability” plots really show – the probability of asthma or the probability to live on a farm?
N Engl J Med 2011;364:701-9 Figure 3 Does it refute any general effect of diversity?
The plots are misleading if adjustment for farm living does not change the parameter estimates for bacterial/fungal diversity.
Sixth – even many years later, the main findings of this study have not been independently replicated. There is not any single study that shows listeriosis (Listeria) or diphtheria (Corynebacterium) to be protective.
Ignoring the long-standing paradox that endotoxin is also acting as a natural adjuvant to atopic inflammation, the credibility of the Science paper is further reduced.
IMHO it is also a strange experimental condition to have all animals on a standard vitamin D diet – a known co-sensitizers – and looking then for A20 which is co-regulated by vitamin D ??
Unfortunately most studies in the farming environment do not report the prevalence of parental history. Neither did they report the effect size of parental genetic risk in the farming population. This is, however, a critical issue as the so called healthy worker effect (HEW) may be a rather trivial explanation of the results.
Specifically, it is a sampling bias: the kind of subjects that voluntarily enroll in a clinical trial and actually follow the experimental regimen are not representative of the general population. They can be expected, on average, to be healthier as they are concerned for their health [or as ill people already dropped out]
Leynaert 2001 showed only a slightly reduced prevalence of “allergy” (39.1% vs 41.5%, NS). Her table 4 is most interesting. The association started only after year 1960 which points towards severe misclassification as far as the analysis is not stratified by year of birth.
Remes 2002 showed a dose dependent effect decline between farming (36.2%) and controls (31.6%, P=0.075),
Perkin 2006 also found some significant lower prevalence in farmers 47.3% versus 57.7%, P<0.001. HWE is therefore likely.
I found further six studies (Thelin 1994, Braback 2006, Chenard 2007, Thaon 2011, Elholm 2013 and Spierenburg 2015) that examined in detail a possible relationship of HWE, allergy and farming. Unfortunately the examination period in five of these studies is too short to make any conclusion while Braback 2006 seems to be the only reliable study.
From this study, we can safely conclude, that there is a significant HWE.
Addendum 22 Nov 2019
It seems that I missed some papers on HWE and farming.
Timm 2019 is a hard to understand cluttered 3 generation study of unclear asthma type. Point estimates of parental asthma on farm upbringing are not really a measure of HWE – shuffling exposure and outcome distorts temporality. In contrast to the interpretation of the authors, I see a clear effect if both parents are born on a farm and one parent has asthma. The RR drops here to 0.33 that their child will be raised on a farm.
Vogelzang 1999: 400 pig farmers, X-sectional point estimates, not a real HWE study, although HWE offered as explanation.
Health-based selection of nonasthmatics for pig farming, which tends to mask a work-related hazard for asthma, is offered as an explanation for these results.
Eduard 2015: compares asthma prevalence of 313 Danish farm children to their 518 sibs (which is identical) but useless, as affected parents would basically dropout all children.
There is even a second comparison of Norwegian farmers with a clear effect. Instead of comparing the early retired farmers with their respective age cohort they invented a c complicated quantile logitic regression in 4 year intervals. Detailed model parameter and significance levels are missing.
At least the conclusion was
A healthy survivor selection was observed in Norwegian farmers, but it was too small to fully explain the reduced risk of asthma observed in this population. A strong selection effect was observed among farmers who had changed production type
The recent encyclopedia article about the hygiene hypothesis seems to be well written. At least on the first instance … in reality it is more a novel than a scientific review.
For many years already, the hygiene hypothesis has been called an outdated concept; various times it was revised and transformed, and finally it gave birth to novel hypotheses.
In other words, the hypothesis has been rejected for being wrong . Even many revisions did not change that. There seem to be only one proven fact – the obsession of some authors with hygiene and nouvel Rousseauism.
Anyway, the hygiene hypothesis has promoted radical rethinking of infections, microbiota, and coevolution of mankind and microbes.
There is nothing radical in backward thinking. We still carry tons of microbes, freezer and antibiotics only did some qualitative but not so much quantitative changes,
With the advent of novel high-throughput sequencing technologies the human microbiome, which is sometimes called the ‘forgotten organ,’ has attracted much attention and is currently being implemented in a wider concept of self-foreign relationship, which may even include recognition of the nonmicrobial nonself as a vital stimulus to a well-developing immune system.
So the interest is technology and not science driven.
The microbiome is not an organ.
The hype is already over.
The Self is not defined by any bacterium.
Most bacteria are excreted and not vital stimulus.
Given the many molecule classes regulating immune functions across individuals such as short RNAs, the hygiene hypothesis may eventually come back as a surprising explanation of the phenomena evoked by crowding, day care, sibship size, orofecally transmitted diseases, and respiratory infections.
Why that?
A comeback of the hygiene hypothesis by short RNA?
The listed phenomena are not intrinsically related, but are occuring only at the same time scale.
Even the old birth order effect might be rediscovered as epigenetic programming someday. Admittedly, these notions are entirely hypothetical, but without hypotheses, proven or not, science hardly advances.
So if David Strachan’s birth order effect would be really caused by epigenetic programming – why would that be related to hygiene at all?
Science is is not so much about proven or unproven but about reasonable and non reasonable hypotheses.
The main arguments in favour of sharing work in its preliminary form are, firstly, that science works faster if work is made available sooner after it is completed and, secondly, that articles are improved by feedback from a wider group of readers, alongside formal peer review by a few experts. Simple estimates suggest that halving the delay to sharing a research result can double the speed at which research progresses. Ambitious research funders are now embracing preprints and other measures that aim to accelerate the pace of research.
MedArXiv will have a hard time attracting preprints if mainstream medical journal editors decide they won’t publish final versions of the papers. Currently, The BMJ and The Lancet are among the few medical journals that have explicitly said that posting a preprint doesn’t preclude publication; Nature and Science, which both occasionally publish medical studies, have the same policy. But at the JAMA Network, which publishes a dozen journals, the issue is hotly debated.
@medRxiv opened on June 6. So far they have only 304 followers on Twitter (and no allergy paper in the archive).
As the current “Allergy” editor and the publisher (John Wiley and Sons A/S) agreed to preprints last week, I have submited now my first preprint paper. Therefore, there are now 305 followers and 1 allergy paper :-)
N Engl J Med 2002; 347:869-877 made a strong point that the farm effect is mediated by endotoxin but could show only a 1,7 fold higher endotoxin exposure at farms.
LPS therefore will not explain the negative farm association as endotoxin effects are so much similar between farming and non-farming environment. BTW why is only the result of the total sample given here and not just the farm result?
N Engl J Med 2011; 364:701-709 table 2 endotoxin effect is not stronger at farms – more some unspecific immunosuppressive effect?
So, what is the reason for the lower IL10 capacity in Figure 2D after LPS exposure – exhaustion, adaptation? And even more important: What is the reason for the lower allergy rate at farms?
If we now go back to table 1 there is a 5,0 fold Der p1 excess in farm – much higher than the 1,7 fold increase of endotoxin. As nearly all allergens have helminth homologues – the question is what did the authors really measure? Da Costa Santiago 2015 has a nice table that could give an answer.
J Immunol. 2015 Jan 1;194(1):93-100 shows Der p1 homologs
Der p1 is a cysteine protease of 25kDa that has homologues for example in Loa loa. Unfortuneately Loa loa is not an explanation at Bavarian farms – as it is more common in tropical Africa. Cysteine proteases are nevertheless a big tool for helminths – in Schistosoma japonicum a cathepsin B2 cysteine protease is considered the main penetration tool.
Usually cysteine proteases are not allergenic, but the excessive (and rather isolated) rise combined with a reduced Der p1 sensitization in the children, is definitely an unusual finding. The Dermatophagoides pteronyssinus habitat is cosmopolitan, house dust, also influenced by altitude, but there is no known reasons for this excess in farms. Is the Der p1 value just a false positive and has it helminthic and not mite origin?
Wormbase blastp results – e+ values are somewhat lower than my local blast result at the same locus
With identity values between 40% and 70% there could well be a confusion of mite Der p1 and helminth (Fasciola?) CL6, which should be tested for cross-reactivity.
Helminth parasites have complicated life cycles … at the same time as skewing the immune system toward a Th2-driven response, they have a general suppressive effect on the host immune system that prevents their elimination and reduces immune-mediated tissue damage. It has been suggested that cytokines of the anti-inflammatory network, particularly IL-10 and transforming growth factor- (TGF-), that are produced in response to continual stimulation of the immune system by parasite antigens, are pivotal to regulating the damage they cause and that, coincidentally, these have a bystander protective affect against allergic reactions.
This is exactly what N Engl J Med 2002; 347:869-877 showed: increasingly exhausted IL10 capacity. May the x-axis label should be CL6 instead of LPS?
N Engl J Med 2002; 347:869-877 Figure 2. Smoothed Plots of the Log-Transformed Capacity of Peripheral-Blood Leukocytes (PBL) to Produce Interleukin-10 (Panel D) after Stimulation with Lipopolysaccharide (LPS) or Staphylococcal Enterotoxin B (SEB) in Relation to the Log-Transformed Endotoxin-Load Values.
