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How the CDC Uses Fear to Increase Demand for Flu Vaccines

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In Brief

  • The Facts:

    The CDC continues to use fear of hospitalization & death to increase demand for flu vaccines. Their "Recipe" calls for encouraging medical experts and public health authorities to “state concern and alarm.”

  • Reflect On:

    Is the flu shot necessary? It's becoming hard to trust health professionals regarding this, especially given the fact their knowledge on vaccines isn't up to par. Independent research might be more effective. It's OK to question vaccines.

The CDC claims that its recommendation that everyone aged six months and up should get an annual flu shot is firmly grounded in science. The mainstream media reinforce this characterization by misinforming the public about what the science says.

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New York Times article from earlier this year, for example, in order to persuade readers to follow the CDC’s recommendation, cited scientific literature reviews of the prestigious Cochrane Collaboration to support its characterization of the influenza vaccine as both effective and safe. The Times claimed that the science showed that the vaccine represented “a big payoff in public health” and that harms from the vaccine were “almost nonexistent”.

-->Listened to our latest podcast episode yet? Joe speaks with journalist Derrick Broze about the need for journalistic standards, Qanon, and agorism. Click here to listen!

What the Cochrane researchers actually concluded, however, was that their findings “seem to discourage the utilization of vaccination against influenza in healthy adults as a routine public health measure” (emphasis added). Furthermore, given the known serious harms associated with specific flu vaccines and the CDC’s recommendation that infants as young as six months get a flu shot despite an alarming lack of safety studies for children under two, “large-scale studies assessing important outcomes, and directly comparing vaccine types are urgently required.”

The CDC also recommends the vaccine for pregnant women despite the total absence of randomized controlled trials assessing the safety of this practice for both expectant mother and unborn child. (This is all the more concerning given that multi-dose vials of the inactivated influenza vaccine contain mercury, a known neurotoxin that can cross both the placental and blood-brain barriers and accumulate in the brain.)

The Cochrane researchers also found “no evidence” to support the CDC’s assumptions that the vaccine reduces transmission of the virus or the risk of potentially deadly complications—the two primary justifications claimed by the CDC to support its recommendation.

The CDC nevertheless pushes the influenza vaccine by claiming that it prevents large numbers of hospitalizations and deaths from flu. To reinforce its message that everyone should get an annual flu shot, the CDC claims that hundreds of thousands of people are hospitalized and tens of thousands die each year from influenza. These numbers are generally relayed by the mainstream media as though representative of known cases of flu. The aforementioned New York Times article, for example, stated matter-of-factly that, of the 9 million to 36 million people whom the CDC estimates get the flu each year, “Somewhere between 140,000 and 710,000 of them require hospitalization, and 12,000 to 56,000 die each year.”

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…the average number of deaths each year for which the cause is actually attributed on death certificates to the influenza virus is little more than 1000.

On September 27, the CDC issued the claim at a press conference that 80,000 people died from the flu during the 2017 – 2018 flu season, and the media parroted this number as though fact.

What is not being communicated to the public is that the CDC’s numbers do not represent known cases of influenza. They do not come directly from surveillance data, but are rather controversial estimates based on controversial mathematical models that may greatly overestimate the numbers.

To put the matter into perspective, the average number of deaths each year for which the cause is actually attributed on death certificates to the influenza virus is little more than 1,000.

The consequence of the media parroting the CDC’s numbers as though uncontroversial is that the public is routinely misinformed about the impact of influenza on society and the ostensible benefits of the vaccine. Evidently, that’s just the way the CDC wants it, since the agency has also outlined a public relations strategy of using fear marketing to increase demand for flu shots.

In other words, the CDC considers it to be a problem that people are increasingly doing their own research and becoming more adept at educating themselves about health-related issues.

The CDC’s “Problem” of “Growing Health Literacy”

Before looking at some of the problems with the CDC’s estimates, it’s useful to examine the mindset at the agency with respect to how CDC officials view their role in society. An instructive snapshot of this mindset was provided in a presentation by the CDC’s director of media relations on June 17, 2004, at a workshop for the Institute of Medicine (IOM).

In its presentation, the CDC outlined a “‘Recipe’ for Fostering Public Interest and High Vaccine Demand”. It called for encouraging medical experts and public health authorities to “state concern and alarm” about “and predict dire outcomes” from the flu season. To inspire the necessary fear, the CDC encouraged describing each season as “very severe”, “more severe than last or past years”, and “deadly”.

One problem for the CDC is the accurate view among healthy adults that they are not at high risk of serious complications from the flu. As the presentation noted, “achieving consensus by ‘fiat’ is difficult”—meaning that just because the CDC makes the recommendation doesn’t mean that people will actually follow it. Therefore it was necessary to cause “concern, anxiety, and worry” among young, healthy adults who regard the flu as an inconvenience rather than something to be terribly afraid of.

The larger conundrum for the CDC is the proliferation of information available to the public on the internet. As the CDC bluntly stated it, “Health literacy is a growing problem”.

In other words, the CDC considers it to be a problem that people are increasingly doing their own research and becoming more adept at educating themselves about health-related issues. And, as we have already seen, the CDC has very good reason to be concerned about people doing their own research into what the science actually tells us about vaccines.

One prominent way the CDC inspires the necessary fear, of course, is with its estimates of the numbers of people who are hospitalized or die each year from the flu.

…many if not most people diagnosed with ‘the flu’ may not have actually been infected with the influenza virus at all, given the large number of other viruses that cause the same symptoms and the general lack of lab confirmation.

The Problems with the CDC’s Estimates of Annual Flu Deaths

Among the relevant facts that are routinely not relayed to the public by the media when the CDC’s numbers are cited is that only about 7% to 15% of what are called “influenza-like illnesses” are actually caused by influenza viruses. In fact, there are over 200 known viruses that cause influenza-like illnesses, and to determine whether an illness was actually caused by the influenza virus requires laboratory testing—which isn’t usually done.

Furthermore, as the authors of a 2010 Cochrane review stated, “At best, vaccines may only be effective against influenza A and B, which represent about 10% of all circulating viruses” that are known to cause influenza-like symptoms. (That’s the same review, by the way, that the Times mischaracterized as having found the vaccine to be “a big payoff in public health”.)

While the CDC now uses a range of numbers to describe annual deaths attributed to influenza, it used to claim that on average “about 36,000 people per year in the United States die from influenza”. The CDC switched to using a range in response to criticism that the average was misleading because there is great variability from year to year and decade to decade. And while switching to the range did address that criticism, other serious problems remain.

One major problem with “the much publicized figure of 36,000”, as Peter Doshi observed in a 2005 BMJ article, was that it “is not an estimate of yearly flu deaths, as widely reported in both the lay and scientific press, but an estimate—generated by a model—of flu-associated death.”

Of course, as the media routinely remind us when it comes to the subject of vaccines and autism (but seem to forget when it comes to the CDC’s flu numbers), temporal association does not necessarily mean causation. Just because someone dies after an influenza infection does not mean that it was the flu that killed him. And, furthermore, many if not most people diagnosed with “the flu” may not have actually been infected with the influenza virus at all, given the large number of other viruses that cause the same symptoms and the general lack of lab confirmation.

The “36,000” number came from a 2003 CDC study published in JAMA that acknowledged the difficulty of estimating deaths attributable to influenza, given that most cases are not lab-confirmed. Yet, rather than acknowledging the likelihood that a substantial percentage of reported cases actually had nothing to do with the influenza virus, the CDC researchers treated it as though it only meant that flu-related deaths must be significantly higher than the reported numbers.

The study authors pointed out that seasonal influenza is “associated with increased hospitalizations and mortality for many diagnoses”, including pneumonia, and they assumed that many cases attributed to other illnesses were actually caused by influenza. They therefore developed a mathematical model to estimate the number by instead using as their starting point all “respiratory and circulatory” deaths, which include all “pneumonia and influenza” deaths.

In his aforementioned BMJ article, Peter Doshi reasonably asked, “Are US flu death figures more PR than science?”

Of course, not all respiratory and circulatory deaths are caused by the influenza virus. Yet the CDC treats this number as “an upper bound”—as though it was possible that 100% of all respiratory and circulatory deaths occurring in a given flu season were caused by influenza. The CDC also treats the total number of pneumonia and influenza deaths as “a lower bound for deaths associated with influenza”. The CDC states on its website that reported pneumonia and influenza deaths “represent only a fraction of the total number of deaths from influenza”—as though all pneumonia deaths were caused by influenza!

The CDC certainly knows better. In fact, at the same time, the CDC contradictorily acknowledges that not all pneumonia and influenza deaths are flu-related; it has estimatedthat in an average year 2.1% of all respiratory and circulatory deaths and 8.5% of all pneumonia and influenza deaths are influenza-associated.

So how can the CDC maintain both (a) that 8.5% of pneumonia and influenza deaths are flu-related, and (b) that the combined total of all pneumonia and influenza deaths represents only a fraction of flu-caused deaths? How can both be true?

The answer is that the CDC simply assumes that influenza-associated deaths are so greatly underreported within the broader category of deaths coded under “respiratory and circulatory” that they dwarf all those coded under “pneumonia and influenza”.

In his aforementioned BMJ article, Peter Doshi reasonably asked, “Are US flu death figures more PR than science?” As he put it, “US data on influenza deaths are a mess.” The CDC “acknowledges a difference between flu death and flu associated death yet uses the terms interchangeably. Additionally, there are significant statistical incompatibilities between official estimates and national vital statistics data. Compounding these problems is a marketing of fear—a CDC communications strategy in which medical experts ‘predict dire outcomes’ during flu seasons.”

Setting aside pneumonia and looking just at influenza-associated deaths from 1979 to 2002, the annual average according to the NCHS data was only 1,348.

Illustrating the problem, Doshi observed that for the year 2001, the total number of reported pneumonia and influenza deaths was 62,034. Yet, of those, less than one half of one percent were attributed to influenza. Furthermore, of the mere 257 cases blamed on the flu, only 7% were laboratory confirmed. That’s only 18 cases of lab confirmed influenza out of 62,034 pneumonia and influenza deaths—or just 0.03%, according to the CDC’s own National Center for Health Statistics (NCHS).

Setting aside pneumonia and looking just at influenza-associated deaths from 1979 to 2002, the annual average according to the NCHS data was only 1,348.

The CDC’s mortality estimates would be compatible with the NCHS data, Doshi argued, “if about half of the deaths classed by the NCHS as pneumonia were actually flu initiated secondary pneumonias.” But the NCHS criteria itself strongly indicated otherwise, stating that “Cause-of-death statistics are based solely on the underlying cause of death … defined by WHO as ‘the disease or injury which initiated the train of events leading directly to death.’”

The CDC researchers who authored the 2003 study acknowledged that underlying cause-of-death coding “represents the disease or injury that initiated the chain of morbid events that led directly to the death”—yet they fallaciously coupled pneumonia deaths with influenza deaths in their model anyway.

At the time Doshi was writing, the CDC was publicly claiming that each year “about 36,000 [Americans] die from flu”, and as seen with the example from the New York Times, the range of numbers is likewise presented as though representative of known cases of flu-caused deaths. Yet the lead author of that very CDC study, William Thompson of the CDC’s National Immunization Program, acknowledged that the number rather represented “a statistical association” that does not necessarily mean causation. In Thompson’s own words, “Based on modelling, we think it’s associated. I don’t know that we would say that it’s the underlying cause of death.” (Emphasis added.)

Of course, the CDC does say it’s the underlying cause of death in its disingenuous public relations messaging. As Doshi noted, Thompson’s acknowledgment is “incompatible” with the CDC’s “misrepresentation” of its flu deaths estimates. The CDC, Doshi further observed, was “working in manufacturers’ interest by conducting campaigns to increase flu vaccination” based on estimates that are “statistically biased”, including by “arbitrarily linking flu with pneumonia”.

…there are otherwise significant limitations of the CDC’s models that potentially result in spurious attribution of deaths to influenza.

More “Limitations” of the CDC’s Models

While the media present the CDC’s numbers as though uncontroversial, there is in fact “substantial controversy” surrounding flu death estimates, as a 2005 study published in the American Journal of Epidemiology noted. One problem is that the CDC’s models use virus surveillance data that “have not been made available in the public domain”, which means that its results or not reproducible. (As the journal Cell reminds, “the reproducibility of science” is “a lynch pin of credibility”.) And there are otherwise “significant limitations” of the CDC’s models that potentially result in “spurious attribution of deaths to influenza.”

To illustrate, when Peter Doshi requested access to virus circulation data, the CDC refused to allow it unless he granted the CDC co-authorship of the study he was undertaking—which Doshi appropriately refused.

While the number of confirmed H1N1-related child deaths was 371, the CDC’s claimed number was 1,271 or more.

In the New York Review of Books, Helen Epstein has pointed out how the CDC’s dire warnings about the 2009 H1N1 “swine flu” never came to pass, as well as how “some experts maintain that the CDC’s estimates studies overestimate influenza mortality, particularly among children.” While the number of confirmed H1N1-related child deaths was 371, the CDC’s claimed number was 1,271 or more. To arrive at its number, the CDC used a multiplier based on certain assumptions. One assumption is that some cases are missed either because lab confirmation wasn’t sought or because the children weren’t in a hospital when they died and so weren’t tested. Another is that a certain percentage of test results will be false negatives.

However, Epstein pointed out, “according to CDC guidelines at the time”, any child hospitalized with severe influenza symptoms should have been tested for H1N1. Furthermore, “deaths in children from infectious diseases are rare in the US, and even those who didn’t die in hospitals would almost certainly have been autopsied (and tested for H1N1)…. Also, the test is accurate and would have missed few cases. Because it’s unlikely that large numbers of actual cases of US child deaths from H1N1 were missed, the lab-confirmed count (371) is probably much closer to the modeled numbers … which are in any case impossible to verify.”

As already indicated, another assumption the CDC makes is that excess mortality in winter is mostly attributable to influenza. A 2009 Slate article described this as among a number of “potential glitches” that make the CDC’s reported flu deaths the “‘least bad’ estimate”. Referring to earlier methods that associated flu deaths with wintertime deaths from all causes, the article observed that this risked blaming influenza for deaths from car accidents caused by icy roads. And while the updated method presented in the 2003 CDC study excluded such causes of death implausibly linked to flu, related problems remain.

As the aforementioned American Journal of Epidemiology study noted, the updated method “reduces, but does not eliminate, the potential for spurious correlation and spurious attribution of deaths to influenza.” Furthermore, “Methods based on seasonal pattern begin from the assumption that influenza is the major source of excess winter death.” The CDC’s models therefore still “are in danger of being confounded by other seasonal factors.” The authors also stated that they could not conclude from their own study “that influenza is a more important cause of winter mortality on an annual timescale than is cold weather.”

Once the CDC has its estimated hospitalization rate, it then multiplies that number by the ratio of deaths to hospitalizations to arrive at its estimated mortality rate. Thus, any overestimation of the hospitalization rate is also compounded into its estimated death rate.

As a 2002 BMJ study stated, “Cold weather alone causes striking short term increases in mortality, mainly from thrombotic and respiratory disease. Non-thermal seasonal factors such as diet may also affect mortality.” (Emphasis added.) The study estimated that of annual excess winter deaths, only “2.4% were due to influenza either directly or indirectly.” It concluded that, “With influenza causing such a small proportion of excess winter deaths, measures to reduce cold stress offer the greatest opportunities to reduce current levels of winter mortality.”

CDC researchers themselves acknowledge that their models are “subject to some limitations.” In a 2009 study published in the American Journal of Public Health, CDC researchers admitted that “simply counting deaths for which influenza has been coded as the underlying cause on death certificates can lead to both over- and underestimates of the magnitude of influenza-associated mortality.” (Emphasis added.) Yet they offered no comment on how, then, their models account for the likelihood that many reported cases of “flu” had nothing whatsoever to do with the influenza virus. Evidently, this is because they don’t, as indicated by the CDC’s treatment of all influenza deaths plus pneumonia deaths as a “lower bound”.

For another illustration, since it takes two or three years before the data is available to be able to estimate flu hospitalizations and deaths by the usual means, the CDC has also developed a method to make preliminary estimates for a given year by “adjusting” the numbers of reported lab-confirmed cases from selected surveillance areas around the country. The “80,000” figure claimed for last season’s flu deaths is just such an estimate. The way the CDC “adjusts” the numbers is by multiplying the number of lab-confirmed cases by a certain amount, ostensibly “to correct for underreporting”. To determine the multiplier, the CDC makes a number of assumptions to estimate (a) the likelihood that a person hospitalized for any respiratory illnesswould be tested for influenza and (b) the likelihood that a person with influenza would test positive.

Caveats such as that, however, are not communicated to the general public by the CDC in its press releases or by the mainstream media so that people can make a truly informed choice about whether it’s worth the risk to get a flu shot.

Once the CDC has its estimated hospitalization rate, it then multiplies that number by the ratio of deaths to hospitalizations to arrive at its estimated mortality rate. Thus, any overestimation of the hospitalization rate is also compounded into its estimated death rate.

One obvious problem with this is the underlying assumption that the percentage of people who (a) are hospitalized for respiratory illness and have the flu is the same as (b) the percentage of those who are hospitalized for respiratory illness, are actually tested, and test positive. This implies that doctors are not more likely to seek lab confirmation for people who actually have influenza than they are for people whose respiratory symptoms are due to some other cause.

Assuming that doctors can do better than a pair of rolled dice at picking out patients with influenza, it further implies that doctors are no more likely to order a lab test for patients whom they suspect of having the flu than they are to order a lab test for patients whose respiratory symptoms they think are caused by something else.

The CDC’s assumption thus introduces a selection bias into its model that further calls into question the plausibility of its conclusions, as it is bound to result in overestimation. In a 2015 study published in PLoS One that detailed this method, CDC researchers acknowledged that, “If physicians were more likely to recognize influenza patients clinically and select those patients for testing, we may have over-estimated the magnitude of under-detection.” And that, of course, would result in an overestimation of both hospitalizations and deaths associated with influenza.

Caveats such as that, however, are not communicated to the general public by the CDC in its press releases or by the mainstream media so that people can make a truly informed choice about whether it’s worth the risk to get a flu shot.

Conclusion

In summary, to avoid underestimating influenza-associated hospitalizations and deaths, the CDC relies on models that instead appear to greatly overestimate the numbers due to the fallacious assumptions built into them. These numbers are then mispresented to the public by both public health officials and the mainstream media as though uncontroversial and representative of known cases of influenza-caused illnesses and deaths from surveillance data. Consequently, the public is grossly misinformed about the societal disease burden from influenza and the ostensible benefit of the vaccine.

It is clear that the CDC does not see its mission as being to educate the public in order to be able to make an informed choice about vaccination. After all, that would be incompatible with its view that growing health literacy is a threat to its mission and an obstacle to be overcome. On the other hand, misinformed populace aligns perfectly with the CDC’s stated goal of using fear marketing to generate more demand for the pharmaceutical industry’s influenza vaccine products.

This article is an adapted and expanded excerpt from part two of the author’s multi-part exposé on the influenza vaccine. Sign up for Jeremy’s newsletter to stay updated with his work on vaccines and receive his free downloadable report, “5 Horrifying Facts about the FDA Vaccine Approval Process”.

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Dive Deeper

These days, it’s not just knowing information and facts that will create change, it’s changing ourselves, how we go about communicating, and re-assessing the underlying stories, ideas and beliefs that form our world. We have to practice these things if we truly want to change. At Collective Evolution and CETV, this is a big part of our mission.

Amongst 100's of hours of exclusive content, we have recently completed two short courses to help you become an effective changemaker, one called Profound Realization and the other called How To Do An Effective Media Detox.

Join CETV, engage with these courses and more here!

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Alternative News

Norway Investigates 29 Deaths in Elderly Patients After Pfizer Covid-19 Vaccination

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In Brief

  • The Facts:

    Norway has registered a total of 29 deaths among people over the age of 75 who’ve had their first Covid-19 vaccination shot, raising questions over which groups to target in national inoculation programs.

  • Reflect On:

    Should freedom of choice always remain here? Should governments and private institutions not be allowed to mandate this vaccine in order to have access to certain rights and freedoms?

What Happened: 29 patients who were quite old and frail have died following their first dose of the Pfizer COVID-19 vaccination. As a result, Norwegian officials have since adjusted their advice on who should get the COVID-19 vaccine.

This doesn’t come as a surprise to many given the fact that the clinical trials were conducted with people who are healthy. Older and sick people with co-morbidities were not used in the trials, and people with severe allergies and other diseases that can make one more susceptible to vaccine injury were not used either. It can be confusing given the fact that vaccination is being encouraged for the elderly in nursing homes and those who are more vulnerable to COVID-19.

Steinar Madsen, medical director of the Norwegian Medicines Agency (NOMA), told the British Medical Journal (BMJ) that “There is no certain connection between these deaths and the vaccine.”

On the 15th of January it was 23 deaths, Bloomberg is now reporting that a total of 29 deaths among people over the age of 75 who’ve had their first COVID-19 shot. They point out that “Until Friday, Pfizer/BioNTech was the only vaccine available in Norway”, stating that the Norwegian Medicines Agency told them that as a result “all deaths are thus linked to this vaccine.”

“There are 13 deaths that have been assessed, and we are aware of another 16 deaths that are currently being assessed,” the agency said. All the reported deaths related to “elderly people with serious basic disorders,” it said. “Most people have experienced the expected side effects of the vaccine, such as nausea and vomiting, fever, local reactions at the injection site, and worsening of their underlying condition.”

Madsen also told the BMJ that,

There is a possibility that these common adverse reactions, that are not dangerous in fitter, younger patients and are not unusual with vaccines, may aggravate underlying disease in the elderly. We are not alarmed or worried about this, because these are very rare occurrences and they occurred in very frail patients with very serious disease. We are not asking for doctors to continue with vaccination, but to carry out extra evaluation of very sick people whose underlying condition might be aggravated by it. This evaluation includes discussing the risks and benefits of vaccination with the patient and their families to decide whether or not vaccination is the best course.

The BMJ article goes on to point out that the Paul Ehrlich Institute in Germany is also investigating 10 deaths shortly after COVID-19 vaccination, and closes with the following information:

In a statement, Pfizer said, “Pfizer and BioNTech are aware of reported deaths following administration of BNT162b2. We are working with NOMA to gather all the relevant information.

“Norwegian authorities have prioritised the immunisation of residents in nursing homes, most of whom are very elderly with underlying medical conditions and some of whom are terminally ill. NOMA confirm the number of incidents so far is not alarming, and in line with expectations. All reported deaths will be thoroughly evaluated by NOMA to determine if these incidents are related to the vaccine. The Norwegian government will also consider adjusting their vaccination instructions to take the patients’ health into more consideration.

“Our immediate thoughts are with the bereaved families.”

Vaccine Hesitancy is Growing Among Healthcare Workers: Vaccine hesitancy is growing all over the globe, one of the latest examples comes from Riverside County, California. It has a population of approximately 2.4 million, and about 50 percent of healthcare workers in the county are refusing to take the COVID-19 vaccine despite the fact that they have top priority and access to it.  At Providence Holy Cross Medical Center in Mission Hills, one in five frontline nurses and doctors have declined the shot. Roughly 20% to 40% of L.A. County’s frontline workers who were offered the vaccine did the same, according to county public health officials. You can read more about that story here.

Vaccine hesitancy among physicians and academics is nothing new. To illustrate this I often point to a conference held at the end of 2019 put on by the World Health Organization (WHO). At the conference, Dr. Heidi Larson a Professor of Anthropology and the Risk and Decision Scientist Director at the Vaccine Confidence Project Emphasized this point, having  stated,

The other thing that’s a trend, and an issue, is not just confidence in providers but confidence of health care providers. We have a very wobbly health professional frontline that is starting to question vaccines and the safety of vaccines. That’s a huge problem, because to this day any study I’ve seen…still, the most trusted person on any study I’ve seen globally is the health care provider.

A study published in the journal EbioMedicine  as far back as 2013 outlines this point, among many others.

Pfizer’s Questionable History:  Losing faith in “big pharma” does not come without good reason. For example, in 2010 Robert G. Evans, PhD, Centre for Health Services and Policy Research Emeritus Professor, Vancouver School of Economics, UBC, published a paper that’s accessible in PubMed titled “Tough on Crime? Pfizer and the CIHR.”

In it, he outlines the fact that,

Pfizer has been a “habitual offender,” persistently engaging in illegal and corrupt marketing practices, bribing physicians and suppressing adverse trial results. Since 2002 the company and its subsidiaries have been assessed $3 billion in criminal convictions, civil penalties and jury awards. The 2.3-billion settlement…set a new record for both criminal fines and total penalties. A link with Pfizer might well advance the commercialization of Canadian research.

Suppressing clinical trial results is something I’ve come across multiple times with several different medicines. Five years ago I wrote about how big pharma did not share adverse reactions people had and harmful results from their clinical trials for commonly used antidepressant drugs.

Even scientists from within federal these health regulatory agencies have been sounding the alarm. For example, a few years ago more than a dozen scientists from within the CDC put out an anonymous public statement detailing the influence corporations have on government policies. They were referred to as the  Spider Papers.

The Takeaway: Given the fact that everything is not black and white, especially when it comes to vaccine safety, do we really want to give government health agencies and/or private institutions the right to enforce mandatory vaccination requirements when their efficacy have been called into question? Should people have the freedom of choice? It’s a subject that has many people polarized in their beliefs, but at the end of the day the sharing of information, opinion and evidence should not be shut down, discouraged, ridiculed or censored.

In a day and age where more people are starting to see our planet in a completely different light, one which has more and more questioning the human experience and why we live the way we do it seems the ‘crack down’ on free thought gets tighter and tighter. Do we really want to live in a world where we lose the right to choose what we do with our own body, or one where certain rights and freedoms are taken away if we don’t comply? The next question is, what do we do about it? Those who are in a position to enforce these measures must, it seems, have a shift in consciousness and refuse to implement them. There doesn’t seem to be a clear cut answer, but there is no doubt that we are currently going through that possible process, we are living in it.

Dive Deeper

These days, it’s not just knowing information and facts that will create change, it’s changing ourselves, how we go about communicating, and re-assessing the underlying stories, ideas and beliefs that form our world. We have to practice these things if we truly want to change. At Collective Evolution and CETV, this is a big part of our mission.

Amongst 100's of hours of exclusive content, we have recently completed two short courses to help you become an effective changemaker, one called Profound Realization and the other called How To Do An Effective Media Detox.

Join CETV, engage with these courses and more here!

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Awareness

Psycho-Acoustic Medicine: Science Behind Sound Healing For Serotonin Production

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In Brief

  • The Facts:

    A number of studies and experiments have shown that sound can be used as medicine for various ailments and diseases.

  • Reflect On:

    Is our modern day medical industry truly interested in the health and well-being of people, or do profit and control take more priority?

Mental illness has reached an all time high in the world, and yet the modern day medicines to relieve symptoms have gained controversy. This is, in part, why people have dug up the past to better understand alternative ways of healing.

Sound, for instance, has been a tool for promoting the physical and emotional health of the body for as long as history can account for, deeply rooted in ancient cultures and civilizations. The ancient Egyptians used vowel sound chants in healing because they believed vowels were sacred. Tibetan monks take advantage of singing bowls, which they believe to be “a symbol of the unknowable” whose “vibrations have been described as the sound of the universe manifesting.”

“Our various states of consciousness are directly connected to the ever-changing electrical, chemical, and architectural environment of the brain. Daily habits of behavior and thought processes have the ability to alter the architecture of brain structure and connectivity, as well as, the neurochemical and electrical neural oscillations of your mind.”

Psychoacoustics is the scientific study of the perception of sound, and it has fueled researchers paths to better understand how it can be used as medicine. For instance, in 1973, Dr. Gerald Oster, a medical doctor and biophysicist, proved, in his research paper, “Auditory Beats in the Brain,” how sound affects the how the brain absorbs new information, controls mood, sleep patterns, healing responses, and more, and how quickly. Thus, specific frequencies of sound and music can be used to generate neurotransmitters such as serotonin.

brain_scan

To understand the fundamentals of sound in healing, we must first understand our brain waves. The nucleus of our thoughts, emotions, and behaviors, is the communication between neurons. Brain waves are generated by way of electrical pulses working in unison from masses of neurons interacting with one another. Brain waves are divided into five different bandwidths that are thought to form a spectrum of human consciousness.

The slowest of the waves are delta waves (.5 to 3 Hz), which are the slowest brain waves and occur mostly during our deepest state of sleep. The fastest of the waves are gamma waves (25 to 100 Hz), which are associated with higher states of conscious perception. Alpha waves (8 to 12 Hz) occur when the brain is daydreaming or consciously practicing mindfulness or meditation.

According to Dr. Suzanne Evans Morris, Ph.D., a speech-language pathologist:

Research shows that different frequencies presented to each ear through stereo headphones… create a difference tone (or binaural beat) as the brain puts together the two tones it actually hears. Through EEG monitoring the difference tone is identified by a change in the electrical pattern produced by the brain. For example, frequencies of 200 Hz and 210 Hz produce a binaural beat frequency of 10 Hz (The difference in 210 Hz and 200 Hz is 10 Hz). Monitoring of the brain’s electricity (EEG) shows that the brain produces increased 10 Hz activity with equal frequency and amplitude of the wave form in both hemispheres of the brain (left and right hemisphere).

It is thought that different brain wave patterns are connected to the production in the brain of certain neurochemicals linked with relaxation and stress release, as well as better learning and creativity, memory, and more. Such neurochemicals include beta-endorphins, growth factors, gut peptides, acetylcholine, vasopressin, and serotonin.

A series of experiments conducted by neuro-electric therapy engineer Dr. Margaret Patterson and Dr. Ifor Capel, revealed how alpha brainwaves boosted the production of serotonin. Dr. Capel explained:

As far as we can tell, each brain center generates impulses at a specific frequency based on the predominant neurotransmitter it secretes. In other words, the brain’s internal communication system—its language, is based on frequency… Presumably, when we send in waves of electrical energy at, say, 10 Hz, certain cells in the lower brain stem will respond because they normally fire within that frequency range.

Additional research upholds the beliefs of mind-body medicine in this sense, stating that brainwaves being in the Alpha state, 8 to 14 Hz, permits a vibration allowing for more serotonin to be created.

It’s important for us to come to terms with the fact that there is science behind age-old medicinal practices that do not require putting unknown substances in our bodies to alleviate issues like stress, depression, anxiety, and more.

But even more intriguing is to think something as simple as sound, as music, which we have come to treat as utterly pleasurable entertainment, has not only been used to promote healing and well-being, but has proven to work through research as well.

If your mental health is of concern, try listening to a binaural beat to generate alpha waves between 8 and 14 Hz to produce more serotonin. Another option is to take advantage of music that promotes a relaxed alpha state in the brain such as classical music.

Related CE Article: Research Shows We Can Heal With Vibration, Frequency & Sound

Dive Deeper

These days, it’s not just knowing information and facts that will create change, it’s changing ourselves, how we go about communicating, and re-assessing the underlying stories, ideas and beliefs that form our world. We have to practice these things if we truly want to change. At Collective Evolution and CETV, this is a big part of our mission.

Amongst 100's of hours of exclusive content, we have recently completed two short courses to help you become an effective changemaker, one called Profound Realization and the other called How To Do An Effective Media Detox.

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Awareness

Study: Short Break From Cosmetics Causes “Significant Drop of Hormone Disrupting Chemicals”

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In Brief

  • The Facts:

    A study led by researchers at UC Berkeley and Clinica de Salud del Valle de Salinas demonstrates how even a short break from certain kinds of makeup, shampoos and lotions leads to a large drop in levels of hormone-disrupting chemicals in the body.

  • Reflect On:

    Why is this industry so poorly regulated?

A study led by researchers at UC Berkeley and Clinica de Salud del Valle Salinas has demonstrated how taking even a short break from various cosmetics, shampoos, and other personal care products can lead to a substantial drop in the levels of hormone-disrupting chemicals present within the body.

The results from the study were published in the journal Environmental Health Perspectives. Researchers gave 100 Latina teenagers various personal care products that were labeled to be free of common chemicals including phthalates, parabens, triclosan, and oxybenzone. These chemicals are used regularly in almost all conventional personal care products such as cosmetics, soap, sunscreen, shampoo, conditioner, and other hair products, and animal studies have shown that they directly interfere with the body’s endocrine system.

“Because women are the primary consumers of many personal care products, they may be disproportionately exposed to these chemicals,” said study lead author Kim Harley, associate director of the UC Berkeley Center for Environmental Research and Children’s Health. “Teen girls may be at particular risk since it’s a time of rapid reproductive development, and research has suggested that they use more personal care products per day than the average adult woman.”

Results

After just a three-day trial with the girls using only the lower-chemical products, urine samples showed a significant drop in the level of chemicals in the body. Methyl and propyl parabens, commonly used as preservatives in cosmetics, dropped 44% and 45%, respectively, metabolites of diethyl phthalate, used often in perfumes, dropped by 27%, and both triclosan and benzophenone-3 fell 36%. The authors of the study were surprised to see an increase in two lesser common parabens, but, being minor, could easily have been caused by accidental contamination or a substitute not listed on the labels.

Co-director of the study Kimberly Parra explains why having local youths participate in the study was of particular importance:

The results of the study are particularly interesting on a scientific level, but the fact that high school students led the study set a new path to engaging youth to learn about science and how it can be used to improve the health of their communities. After learning of the results, the youth took it upon themselves to educate friends and community members, and presented their cause to legislatures in Sacramento.

Included in the CHAMACOS Youth Council were 12 local high school students who helped design and implement the study. One of the teen researchers, Maritza Cárdenas, is now a UC Berkeley undergraduate majoring in molecular and cell biology.

“One of the goals of our study was to create awareness among the participants of the chemicals found in everyday products, to help make people more conscious about what they’re using,” said Cárdenas. “Seeing the drop in chemical levels after just three days shows that simple actions can be taken, such as choosing products with fewer chemicals, and make a difference.”

The researchers noted that cosmetics and personal care products are not well-regulated in this country, and that getting data about health effects from exposure, particularly long-term ones, is difficult. But they say there is growing evidence linking endocrine-disrupting chemicals to neurobehavioral problems, obesity and cancer cell growth.

What Can You Do?

Well, you can be sure to check the labels on any products you purchase. Most personal care products contain a list of ingredients, but unfortunately many cosmetics do not. If you use a particular brand that you really love you can try contacting the manufacturer directly and asking them for an ingredient list.

You can also opt for more natural and organic products, but be sure to keep in mind that in the industry of personal care products, the words “natural” and “organic” are often meaningless. A safe bet would be to buy these products from a health food store and be sure to read the ingredients or ask the sales clerk. Generally, when products do not contain specific chemicals, the manufacturers are happy to label them as such.

The less demand for these chemically-laden products there is, the less these chemicals will be used. I’ve said it before and I’ll say it again: VOTE WITH YOUR DOLLAR! We have the power to create the type of world we want. Be the change.

Check out The Story Of Cosmetics below!

Dive Deeper

These days, it’s not just knowing information and facts that will create change, it’s changing ourselves, how we go about communicating, and re-assessing the underlying stories, ideas and beliefs that form our world. We have to practice these things if we truly want to change. At Collective Evolution and CETV, this is a big part of our mission.

Amongst 100's of hours of exclusive content, we have recently completed two short courses to help you become an effective changemaker, one called Profound Realization and the other called How To Do An Effective Media Detox.

Join CETV, engage with these courses and more here!

Continue Reading
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