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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”.

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”.

Sign up for free news and updates from Robert F. Kennedy, Jr. and the Children’s Health Defense. CHD is planning many strategies, including legal, in an effort to defend the health of our children and obtain justice for those already injured. Your support is essential to CHD’s successful mission.

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Awareness

Man Fasts For 382 Days Straight & Loses 276 Pounds

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In Brief

  • The Facts:

    Angus Barbieri, a man who, in June of 1965, began a fast under medical supervision for exactly 382 days. He remained completely healthy for the duration of the fast.

  • Reflect On:

    Today, it's firmly established in scientific literature that fasting can have tremendous benefits, if done correctly. It can also be used to treat a variety of diseases. Perhaps it's not emphasized because you can't make money off of not eating?

A study published in the Post Graduate Medical Journal in 1972 brought more attention to a gentleman by the name of Angus Barbieri, a man who, in June of 1965, began a fast under medical supervision for exactly 382 days and, at the time the study was published, had since maintained his ordinary weight. In his case, “prolonged fasting had no ill effects.” Barbieri’s weight decreased from 456 to 180 pounds during the fast.

This isn’t the only example that’s available in the literature, it’s similar to an earlier patient prior to Barbieri who reduced his weight from 432 to 235 pounds during 350 days of intermittent fasting (Stewart, Fleming & Robertson, 1966). Researchers have also fasted patients for 256 days (Collison, 1967, 1971), 249 and 236 days (Thomson et al., 1966) as well as  210 days (Garnett et al., 1969; Runcie & Thomson, 1970), all of which are cited in the 1972 study.

Since the publication of this time, there are many documented examples of prolonged fasting done by highly obese people. Here’s one recent example of a man who fasted for 50 straight days, while being medically supervised and tested the whole time.

When you fast, your body switches from burning glucose, to burning fat. Fasting lowers insulin levels which allows the body to access its fat stores for energy. When you eat, food is converted into glucose and that’s what we usually burn. This is why fasting has become a therapeutic intervention for many people with type two diabetes, and more doctors, like Dr. Jason Fung, a Toronto Based nephrologist, are having great success with utilizing fasting as an appropriate and necessary health intervention. Fung has many great articles regarding the science of fasting, you can access them here if you’re interested in learning more. This article references some of the leading scientists in the field so you can learn more by looking them up as well.

The graph below depicts what happens to your protein while fasting. Interesting isn’t it? People often believe that if you fast, you will experience a tremendous amount of muscle loss during fasting, but that’s simply not true. This graph is from Kevin Hall, from the NIH in the book “Comparative Physiology of Fasting, Starvation, and Food Limitation.”

“It seems that there are always concerns about loss of muscle mass during fasting. I never get away from this question. No matter how many times I answer it, somebody always asks, “Doesn’t fasting burn your muscle?” Let me say straight up, NO.”  – source Dr. Jason Fung

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But what about Angus Barbieri? Obviously we’re not saying long term fasts for this long are healthy, obviously for many people they will probably be unhealthy and unsafe unless medically supervised. In  the 1972 study doctors measured a number of concentrations within the body. For example, plasma potassium concentrations over the first four months decreased systematically. As a result, they provided a very small daily dose that increased his potassium level. After another 10 weeks, no potassium was given, and from there on in until the end of the fast, plasma potassium levels remained normal. Cholesterol concentrations also remained around 230 mg/ 100 ml until 300 days of fasting, but increased to 370 mg/100 ml during refeeding.

Plasma magnesium levels decreased over the first few weeks of the fast but then went up and stabilized. This is interesting to note as there is nothing going into the body, yet levels still stabilized after the initial decrease.

Normal plasma magnesium concentrations, despite magnesium ‘depletion’ in muscle tissue, have been described (Drenick et al., 1969) during short-term fasting (1-3 months). The only other relevant report is a remark (Runcie & Thomson, 1970) that one patient who fasted 71 days had a normal plasma magnesium level of 2-2 mEq/l at the time when she developed latent tetany. The decrease in the plasma magnesium concentration of our patient was systematic and persistent.

Furthermore:

The excretion of sodium, potassium, calcium and inorganic phosphate decreased to low levels throughout the first 100 days, but thereafter the excretion of all four urinary constituents, as well as of magnesium, began to increase. During the subsequent 200 days sodium excretion, previously between 2 and 20 mEq daily, reached over 80 mEq/24 hr, potassium excretion increased to 30-40 mEq daily and calcium excretion increased from 10-30 mg/24 hr to 250- 280 mg/24 hr. Magnesium excretion (which was not measured during the first 100 days) reached 10 mEq/ 24 hr between Days 200-300. Phosphate excretion, which had decreased to under 200 mg/24 hr, also increased to around 800 mg/24 hr, even exceeding 1000 mg/24 hr on occasion. Peak excretions of all these constituents were seen around Day 300, after which there was a marginal decrease, but excretion remained high.

Obviously, this is an extreme fast and such fasts have only been tested on people of tremendous obesity, and it shows that people with a high body fat percentage have the ability to fast longer simply because their body has more stores to pull from.

The study concluded in 1972 that:

We have found, like Munro and colleagues (1970), that prolonged supervised therapeutic starvation of the obese patient can be a safe therapy, which is also effective if the ideal weight is reached. There is, however, likely to be occasionally a risk in some individuals, attributable to failures in different aspects of the adaptative response to fasting. Until the characteristics of these variations in response are identified, and shown to be capable of detection in their prodromal stages, extended starvation therapy must be used cautiously. In our view, unless unusual hypokalaemia is seen, potassium supplements are not mandatory. Xanthine oxidase inhibitors (or uricosuric agents) are not always necessary and could even be potentially harmful (British Medical Journal, 1971) perhaps particularly in the long-term fasting situation.

It’s almost 2020, and the literature, studies and research that’s been published since 1972 is vast. We’ve learned a lot more about it and if done correctly it can be extremely beneficial. Shot term fasting  presents minimal to no health risks, and so does long term fasting that lasts more than 24 hours, that is unless a person already has an underlying condition. That being said, it’s not easy to start. Most people are used to eating three meals plus snacks every single day, therefore they are never adapted to burning their fat stores, something that appears the human body was meant to do.

“Why is it that the normal diet is three meals a day plus snacks? It isn’t that it’s the healthiest eating pattern, now that’s my opinion but I think there is a lot of evidence to support that. There are a lot of pressures to have that eating pattern, there’s a lot of money involved. The food industry — are they going to make money from skipping breakfast like I did today? No, they’re going to lose money. If people fast, the food industry loses money. What about the pharmaceutical industries? What if people do some intermittent fasting, exercise periodically and are very healthy, is the pharmaceutical industry going to make any money on healthy people?” – Mark Mattson (source)

Fasting has also been shown to be effective as a therapeutic intervention for cancer. Fasting protects healthy cells while ‘starving’ cancer cells, it’s now being used as an intervention that’s being combined with chemotherapy. Fasting has also been shown to greatly reduce the risk of age related diseases like Parkinson’s Disease, and Alzheimer’s disease. Mark Mattson, one of the foremost researchers of the cellular and molecular mechanisms underlying multiple neurodegenerative disorders has shown through his work that fasting can have a tremendous effect on the brain, and can even reverse the symptoms of multiple neurodegenerative disorders. You can watch his interesting TED talk here.  Scientists have also discovered strong evidence that fasting is a natural intervention for triggering stem cell-based regeneration of an entire organ or system.

Fasting has actually long been known to have an effect on the brain. Children who suffer from epileptic seizures have fewer of them when placed on caloric restriction or fasts. It is believed that fasting helps kick-start protective measures that help counteract the overexcited signals that epileptic brains often exhibit.  (source)

The list goes on and is quite long. At the end of the day if you do your research, fasting, under proper medical supervision, can have tremendous health benefits that go far beyond what’s mentioned in the paragraph above. Every single study that has looked at fasting as a therapeutic intervention for several diseases has shown nothing but positive benefits. Even studies conducted regarding caloric restriction, something completely different than fasting, have shown promising results in all animal models.

According to a review of fasting literature conducted in 2003, “Calorie restriction (CR) extends life span and retards age-related chronic diseases in a variety of species, including rats, mice, fish, flies, worms, and yeast. The mechanism or mechanisms through which this occurs are unclear.” Since this study was published, a great amount of research has been conducted from many researchers, and the mechanisms are being discovered and have become more clear. If you want to further your research, apart from the names listed above, Dr. Valter Longo and his research is another great place to start.

The body has a tremendous amount of storage, and it hangs on to what it needs during a fast, and uses up ‘bad’ things, repairs damaged cells, and more. When you fast and deplete all your glycogen, your body is going to start using fat for energy, it’s going to use damaged cells for energy, it’s basically going to use all of the bad things first, before it gets to the good thing…Your body will not burn protein, as protein is not a fuel source while fasting.

I bring this up because it’s interesting to see what the body loses and hangs on to during a fast.

The Takeaway

The truth about fasting is that it’s not dangerous at all. Intermittent fasting and short term fasting can be done by just about anybody. From what we’ve seen with regards to prolonged fasting, it’s also not very dangerous when it comes to obese people doing it under medically supervised conditions. Theoretically, based on the science alone, any relatively healthy human being should be able to do a prolonged fast without any harmful consequences.

Obviously, prolonged fasts that are not medically supervised can be very detrimental. We are obviously not recommending this and you must do a lot of research and talk to your doctor if you’re interested in fasting, before trying it. For starters, a little bit of intermittent fasting here and there is a no brainer, and not dangerous at all if you have no underlying health conditions, but everybody’s body is different.

Fasting is making a lot of noise, and has been making a lot of noise within the health community, but it’s still not appropriately taught and used by the mainstream medical industry. Why is this so? The answer is simple, you can’t make money off of fasting.

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Alternative News

Thousands Gather To Mark The 33rd Anniversary of the National Childhood Vaccine Injury Act

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Government’s gift to Pharma of liability-free vaccines puts children’s health at risk states Children’s Health Defense (CHD) Chairman, Robert F. Kennedy, Jr.

Washington, DC – Thousands of advocates for children’s health will gather Thursday at the Vaccine Injury Epidemic (VIE) Event on the National Mall to mark the 33rd anniversary of National Childhood Vaccine Injury Act (NCVIA). The rally on Nov. 14th will spotlight the devastating impact NCVIA has had upon the state of children’s health. While children continue to be injured by vaccines daily, vaccine makers cannot be held accountable, thereby eliminating incentive for vaccine safety.

In his remarks, RFK, Jr. will address the ramifications of NCVIA and honor those whose lives have been impacted by vaccine injury and death. “It’s time to call out Congress, the CDC, and drug companies for allowing industry profits to trump children’s health,” said Kennedy. “There is no crisis more urgent than the epidemics of chronic health conditions among our nation’s children.”

Following NCVIA’s passage creating the National Vaccine Injury Compensation Program (NVICP), the childhood vaccine market sparked a gold rush for Pharma as more vaccines for routine childhood illnesses were developed. Coterminous with the burgeoning vaccine schedule, chronic health conditions in children rose from 12% to 54%. As vaccine industry profits grew to $50 billion annually, so did diagnoses of asthmaautismADHDallergiesanxietydepressiondiabetesobsessive-compulsive disorder and auto-immune diseases.  Here are the facts:

  • An HHS-funded study found only 1% of vaccine injuries are reported.
  • Despite NVICP’s high burden of proof and two out of three claims dismissed, over $4.2 billion has been paid for claims of vaccine injury or death.
  • The vaccine-injured find NVICP to be a years-long, litigious program with no jury, discovery and precedent. While medical bills mount, the injured are up against DOJ lawyers and HHS “Special Masters” that act as judges.
  • The Department of Justice and the NVICP are accused of fraud and obstruction of justice in the Autism Omnibus Proceeding.
  • The Institute of Medicine reports that the vaccine schedule as recommended has never been studied for long-term health effects despite independent research suggesting that unvaccinated children are healthier.
  • Modern medicine acknowledges that not everyone responds the same to vaccination and the “one size fits all” vaccine policy is not science based.

Children’s Health Defense’s created these six steps to vaccine safety. RFK, Jr. interviews are available upon request.

Sign up for free news and updates from Robert F. Kennedy, Jr. and the Children’s Health Defense. CHD is planning many strategies, including legal, in an effort to defend the health of our children and obtain justice for those already injured. Your support is essential to CHD’s successful mission.

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Awareness

How To Clear Seriously Blocked Sinuses Naturally In 1 Minute

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In Brief

  • The Facts:

    Three simple steps you can take to clear blocked sinuses that seem to work for many people.

  • Reflect On:

    Are you healthy? What natural things do you do when "flu season" comes around to give your immune system a boost?

Having clogged sinuses isn’t fun. You can’t breath, you can’t smell, your head hurts, and your voice sounds funny. Finding relief when you have clogged sinuses is usually like finding a million dollars on the ground — it’s amazing!

The causes for nasal congestion can range greatly, and you don’t have to be sick to be congested. Many people will experience congestion from allergies, temperatures, dust, smoking, spicy food, and air particles.

Recently I was at Contact in the Desert in California and I found myself having clogged sinuses from the blowing sand and dry air. Within two days, I couldn’t breathe at all out of one side of my nose and my sinuses got blocked up, causing my face and head to hurt. I needed a solution.

After trying to blow my nose over and over again, I turned to the internet for relief. Sure enough, Google came through.

I found a video by Dr. Adam that quickly and easily explained how to clear sinuses in about one minute using just your fingers — and no, they don’t have to go in your nose. Sure enough, I had relief from the pain the blockage was causing, and I could breathe!

Some might be wondering why I didn’t take sinus or cold medication to get relief. The answer is simple: I don’t like taking medication for anything unless I absolutely have to. I know many of you are on the same page and like to do things naturally. Many cold medications just mask symptoms and come with negative side effects that are worth avoiding if possible.

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How to Clear Your Sinuses Fast!

You simply need to sit down and get your hands ready for the following steps. The video below offers a visual demonstration, so I recommend checking that out too.

1. While sitting with your head and body on about a 45 degree angle, turn your head sideways and rub your sternocleidomastoid muscle downward four or five times. You can find the muscle right beneath your ear running down your neck to your collarbone. See image. Do this on both sides of your neck to help relax your neck.

2. Take your index fingers, locate the hard, bony part of the upper sides of your nose, and move downward toward the soft part on the side of your nose where the bone ends. Begin massaging this area in a circular motion with as much pressure as you can for about 20 seconds. Once completed, rub the muscles from the side of your nose down and toward your cheekbones to relax them.

3. Take your index fingers and run them under the inside orbit bone above your eyes until you find a notch in the bone called the super orbital notch. It is usually just above the centre of the eye. Massage that notch in a circular motion with as much pressure as you can handle for about 20 seconds. Once done, massage your forward with both hands starting in the centre of your forehead and pulling outwards towards your temples.

That’s it! Once you have gone through this process you should notice a lot of relief in your sinuses and should be able to blow your nose quite easily. You may have to repeat this process again, but play with it and see what works for you.

Below is a video from Dr. Adam explaining the entire process. I have also included another helpful method that worked well for me as well.

Alternative Method

This method is simpler but may not be as effective for everyone. As always, do what works best for you.

1. Push your tongue flat into the roof of your mouth, with decent pressure, for one second.

2. Then, take your thumb and press the area right between your eyebrows above your nose for one second.

3. Alternate between steps one and two over and over again for about 20-30 seconds. Note: You are not pressing the points at the same time, simply alternating between them.

Repeat this process as necessary to help clear your sinuses.

Prevention

If you’ve had blocked sinuses, you probably don’t want it to happen often, so prevention is the key! Here are a few ways you can avoid blocked sinuses.

Eat a well-balanced diet – Eating healthy foods promotes good health. What you put into your body to digest is what determines your health. If you want your immune system working well, take care with quality food and keep your gut performing well.

Get regular exercise – Regular exercise also helps improve overall health and the immune system.

Quit smoking – It goes without saying, but cigarettes are not good for us and the smoke can irritate sinuses.

Use a humidifier – If you find your house dry, use a humidifier to help dampen the air. You can also hop in a warm shower and breathe in the steam. It’s best to use a chlorine filter on your shower head so you aren’t breathing in toxic chemicals from chlorine.

Cut out antibiotics – Antibiotics don’t do anything for viral infections, which is usually why people get clogged sinuses when they are sick. Antibiotics wreak havoc on your health. Only take them when they are absolutely necessary!

Keep a clean home – Dust and poor air quality can also cause blocked sinuses. Vacuum and wipe down surfaces of your home regularly. Decrease clutter and areas where dust can collect and stay.

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