Thanks, the IPUMS website looks very intriguing! Maybe it'll allow me to make a comprehensive datasets of lot of variables to test.
In terms of the variables you mentioned, I think NATORIGIN might have stopped being asked before CHRFATIGEV was started.
NATORIGIN: 1976-1977, 1987, 1992...
Prevalence of severe fatigue after SARS-CoV-2 infection in Norway: a prospective 2-year follow-up study
Objectives
This study aims to estimate the prevalence of long-lasting severe fatigue and identify possible risk factors in a 2-year follow-up of patients with predominantly mild-to-moderate...
Metacognition and cognitive dysfunction in post-COVID condition
Background
The mechanisms associated with cognitive issues in post-COVID condition (PCC) are still under debate. Metacognition refers to the ability to reflect and evaluate one’s cognitive functioning and remains unexplored in...
Good question.
Just to check how well "tired" and "why am I so tired" correlate to English ancestry, I tested those too with the Google trends data from 2004 to present.
R2=0.11 for "tired" and R2=0.16 for "why am I so tired". So there's a correlation there too, albeit weaker than for ME/CFS.
An AI gave me some more ideas for what may be driving the association: living in a rural area and having access to internet.
So I downloaded data for those two and included them along with education, income, language, and English ancestry into one regression. But alas, English ancestry remains...
Cascading Ion Transport Impairment: A Sequential Vulnerability Framework for Gulf War Illness
Ford, Jeffrey S
Abstract
Gulf War Illness affects an estimated 25 to 32 percent of the 700,000 United States military personnel deployed to the 1990 to 1991 Persian Gulf War (Steele et al., 2024)...
None of the efficacy outcomes were pre-registered with ClinicalTrials.gov. Only these:
Primary
Proportion of Successfully Completed Treatments
Secondary
Device comfort
Device ease of use
Clarity of instructions
I realized the main reason I got a smaller R2 value was because I used the trend values based only on the last year of search data, while Murph used the data based on searches from 2004 to present. From the blog post:
In my view, if a study describes itself as exploratory and does not do multiple test correction, then what it is saying is that no efficacy conclusions can be drawn from the data, where instead the results are meant to be used as a reference for seeing if the most significant findings replicate...
They asked about many ancestries. I checked the associations with all of them in these two posts:
- https://www.s4me.info/threads/a-crumb-of-a-clue-on-epidemiology.49455/post-682605
- https://www.s4me.info/threads/a-crumb-of-a-clue-on-epidemiology.49455/post-682794
For comparison, here are the plots for association of 5 year search data for the ME/CFS topic with English ancestry and education:
Interestingly, if instead using the specific search term "chronic fatigue syndrome" over the same time frame, the association with English ancestry gets stronger...
I like your thinking.
I used the 2024 5-year average S1501 "Educational Attainment" dataset, specifically the column for percent of those at least 25 years old that have a bachelor's degree.
Same 5-year English ancestry and 1-year Trends data as before.
There does seem to be a correlation of...
If you highlight text, there should be a popup like this:
Pressing Reply instantly adds it to the message box as a quote.
Pressing Quote adds it to a hidden list of quotes that you can then insert into the message box with the "Insert Quotes" button that appears near the message box.
Hm. I really thought it might be that people with higher income search ME/CFS more, as they might have better access to resources that would make them aware of what ME/CFS is. And maybe states with larger proportions of Northern European or British ancestry would have higher average income.
But...
This page seems to suggest that if you are looking at a simple search term, then it will show trends just for that specific term in that language. But if you search by a "Topic", then it tracks trends across different translated versions of that topic.
-...
This was showing lots of UK countries at the top, and I realized that it may be because people could report multiple ancestries.
From an overview of these datasets:
I (and I think Murph) used B04006, which counts up to two ancestries per person. So, for example, the correlations for Scottish...
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