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Sek Kathiresan MD
@skathire
, 7 tweets, 2 min read Read on Twitter
Astounding fact I learned today:

Weight of average adult US male

1960: 166 pounds
2002: 191 pounds

😬
Weight of average adult US female

1960: 140 pounds
2002: 164 pounds
OK.

For all the people who think these trends are because the US has become taller:

🤦

average height US

1960: 5ft 8in (male); 5ft 3in (female)
2002: 5ft 9in (male); 5ft 4in (female)
link: cdc.gov/nchs/data/ad/a… …

table below
Graphic over 30 years.

Interesting to see greater spread over time.
IMO, most consequential plot for future of US health is 👇🏽

Why did this happen?
What can we do to retard this march?
Coda:

Stats updated to 2016 for weight:

Men: 166 lb (1960) to 191 (2002) to *198 lb* (2016)

Women: 140 lb (1960) to 164 (2002) to *171 lb* (2016)

😳
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More from @skathire see all

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Sek Kathiresan MD
@skathire
👇🏽 what I hope will be our most impactful discovery to date

An enzyme whose loss of function lowers blood cholesterol & *protects* against fatty liver & cirrhosis

Kudos to @connoremdin whose clever analysis of public data (@ukbiobank) led to observation

biorxiv.org/content/10.110…
Here's the story of the discovery:

@connoremdin noticed that gene variants affect cirrhosis in same direction, similar effect size regardless of underlying etiology (fatty liver, alcohol, viral)
And so, idea: combine all causes of cirrhosis into a single new case definition and perform genetic analysis
Read 10 tweets
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Sek Kathiresan MD
@skathire
Excited about real-world data (ie, electronic health records) for causal inference? a cautionary tale👇🏾

in @uk_biobank analysis LDL extremes & risk for future coronary disease (one of surest causal relationships in medicine) by @jpirruccello yields:
WRONG ANSWER

What happened?
Answer: confounding based on LDL-lowering treatment at entry into @uk_biobank

(L) plot without accounting for lipid-lowering therapy

(R) plot after accounting for lipid-lowering therapy at baseline (about 17% of participants on lipid-lowering Rx at entry)
Large scale data-analyses with millions of real world evidence data points,

just imagine all the false causal inference claims that we can look forward to!!

😳
Read 4 tweets
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Sek Kathiresan MD
@skathire
Met with postdoc keen on staying in academia & applying for faculty jobs

I asked: "Have you put together a Description of Research Activities?"

👇🏽mine from April 2007 as I was just finishing my research training & applying for research faculty positions

Some thoughts...thread.
rest of document...
Start with:

1. what important question(s) do you want to address over first 5y of faculty position
2. what tools/approaches will you use to address question(s)

need to be able to articulate this clearly in one page - "a specific aims page for your research life"
Read 12 tweets

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And just like that you see the CNN lie.

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How gender identity politics is endangering #WomensRights masquerading under the guise of “progressivism”- or in other words, as I said to this @notokyriarchy fatherfucker, an #MRA’s dream come true
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Tunde Eneji
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My Dear Igbo Compatriots, your leaders, not President Buhari, are your enemies

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Politics anywhere in the world is a fierce battle. Like war, all is fair in politics. In Nigeria, tribe & religion determine, to a very extent, political victories

I wonder if the above assertion is debatable. I have seen a lot to come to this conclusion
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Like all mortals, PMB has his weaknesses and these weaknesses have been over-exaggerated by his political foes

That's politics!!
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Eric Electron
@ericelectron2
#Fact 1 - The Wage Gap is real. People who says it's not haven't read the data.

However, in places like the USA, the wage gap is *not* mostly due to sexism like many #femnist #WomenInScience are claiming it is today. Disparate outcomes doesn't imply disparate treatment.
Women typically choose fields that are lower paying; even in the #STEM fields. To attribute that to sexism only or even mostly is a very dishonest way of deriving an answer for this complex disparity.

Sources:

cew.georgetown.edu/wp-content/upl…

npr.org/sections/money…
When the US Department of Labor Statistics took into consideration personal choices, non-wage benefits, hours worked, experience, education, and other variables that contributes to the wage gap the percentage of earnings decreases to approximately 3%.

shrm.org/hr-today/publi…
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