I recently asked my readers to tell me about their chronic health conditions.
The single most important conclusion is this
In all 58 conditions we asked about where we had sufficient data to compute an odds ratio, the vaccine always made the condition worse.
In other words, the medical community has gotten it backwards for decades. When you combine this with the realization that vaccines provide a benefit that is too small to measure as described here for the highly acclaimed COVID and flu vaccines, it’s clear that we should be stopping most, if not all, vaccines.
In fact, for the COVID vaccines, we have FOIA data showing that the vaccines make things worse and over a dozen attempts to ask the Santa Clara County of Public Health for comment have been ignored.
This is fundamentally why the NIH will never do a study comparing the highly vaccinated to the completely unvaccinated: it would blow the narrative and destroy their credibility.
Other important results of the survey include:
3.3X higher likelihood you’ll have 1 or more chronic diseases (OR 3.45 [95% CI: 3.02-3.96]). The one-sided p-value was 1.6e-78, something you don’t see very often. It basically means that this was not caused by random chance.
7X higher likelihood you’ll have 5 or more chronic conditions requiring treatment (drugs or therapies) (OR 7.03 [95% CI: 4.24-12.32]).
4X higher likelihood of a birth defect if the mother was vaccinated during the pregnancy (OR 4.31 [95% CI: 2.39-7.51]). That’s a huge effect. Nearly 80% of the birth defects are caused by the mother being vaccinated during pregnancy (actual value is 76.8%).
14.5X higher likelihood of sexual orientation/gender dysphoria issues in people under age 60 (OR 14.49 [95% CI: 2.33- 598.86]). This is a stunning result that isn’t discussed. Basically, 93% of the cases of sexual orientation issues are caused by vaccines.
The good news is that we can reduce chronic diseases in America by 70% with one simple change: tell people to stop taking the vaccines that are making them sick. That’s it. No new medications are needed. Just one policy change communicated from the CDC. It could literally happen tomorrow. It costs nothing.
And there needs to be full data transparency about all these vaccines so people can see how badly they were fooled.
The efficacy data for all vaccines is easy to gather, but we aren’t allowed to access the data to do the studies. This article shows how easy it is to expose the fraud. This research can be replicated for every disease if the government made the data available.
Over 13,000 responses, average age=55
Breakdown of the two comparison groups I used in the analysis:
Fully unvaccinated: 2,355 responses, average age=55
Highly vaccinated: 2,260, average age = 49
63 conditions tested
44 conditions had odds ratio (OR) >=2 which means vaccines are the single largest cause of that condition
14 conditions had OR of 1.3-2.0 which means vaccines are a significant cause of that condition (23% of the cases or more are attributable to vaccination)
The remaining 5 conditions had insufficient data to compute an odds ratio (p-value >.05).
Here is the list of symptoms and the odds ratios and p-values. Values >1 mean the vaccines made people less healthy. p-values of >.05 mean the result is not statistically significant.
Lines 61 and below have a p-value >.05 and are NOT statistically significant (because the effect is too small or the number of samples are too small or both).
I did a similar survey of 10,000 kids of my readers. You can compare the effect sizes in that survey vs. this survey.
But basically, the results there were the same as here: vaccines made things worse.
Unlike papers in the peer reviewed literature, my data and analysis is available for public inspection. This is a novel concept that is frowned on by the medical community which is why they rarely do it.
Article announcing the survey March 29 at 6:52pm PST.
Survey form
Responses (these are updated live)
Excel spreadsheet analysis with OR calculation, p-values, and 95% confidence intervals (note: when you click this link, it will silently download the spreadsheet to your Downloads folder).
I blanked out the age field of 18 entries where age field >102 or more. This was likely user entry error.
Some of the wording was changed during the course of the survey to make things more clear.
Some new symptoms were added during the survey, but this doesn’t affect the odds calculations; the raw incidence rates would not be accurate for these. Raw incidence rates were not used in the analysis.
I collected over 10,000 responses in < 24 hours from launch.
The average age of all respondents was 55 and was 49 for the fully vaccinated, so these adults reporting they are fully vaccinated are undervaccinated compared to kids nowadays.
This means that our kids will be negatively impacted more than the (mostly) adults in our survey.
So these odds ratios should be conservative.
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