Uncertain Health in
an Insecure World – 34
“Mark Twain Turns 180”
Epidemiology is old school science. Associations between
human characteristics and diseases, even when statistically significant, are
not proof of cause and effect. As Mark Twain once put it, “There are lies, damn lies and statistics”. When so-called “weak effects” data make it to the pages
of high impact journals, they assume great significance in the minds of
readers.
Here are some recent studies from the epidemiology research
space.
The United Kingdom Clinical Practice Research Datalink
recorded characteristics of 2,000,000 people aged 40+ between 1992 and 2007,
with a median age of 55 years, of which 55% were female. As reported in The Lancet, of these individuals, a
total of 45,000 developed dementia during the period of observation – 2.4 cases
per 1,000 patient years. In this cohort, obese subjects (BMI ≥30) were at
lowest risk of future dementia, while underweight subjects (BMI <20) had the
greatest risk – 34% greater than those with normal weight. By age 80 years, the
incidence of dementia was 9.9% for underweight people versus 4.9% for obese
people.
I'm not sure what to make of this so-called “obesity paradox”.
I'm not sure what to make of this so-called “obesity paradox”.
WHO reports that of 36 million annual deaths worldwide from
non-communicable diseases, nearly 8 million are from cancer. The American
Cancer Society estimates that one in three cancers in the U.S. are linked to
excess body weight, where diet and physical inactivity are thought to be contributors.
Evidence points to greater prostate cancer risk and poorer post-surgical
outcomes in obese men, especially among African-Americans. A large European
study (EPIC) showed that greater height and obesity are associated with an
increased risk of breast cancer in post-menopausal women – for every 5 kg
gained, the risk increased 8%; hormone therapy was partially protective in
women with a BMI >30. The Women’s Health Initiative followed 161,809 women
from 1998 to 2006, showing that there was an inverse association between lower
BMI and higher lung cancer risk in smokers.
Enter the new school science of gene sequencing, or
genomics.
A study in The New
England Journal of Medicine on the DNA of 65,066 people with coronary
artery disease (CAD) compared to 128,383 controls showed that CAD risk
increased by 13.5% for each 2.5 inch drop below the average height. ‘Bad’ LDL
cholesterol and triglyceride levels were found to statistically account for
only 31% this increased short-stature risk. The accepted theory had been that
larger people have wider arteries, so that plaques are not as occlusive. Of some
180 DNA sequences in the human genome known to contribute to height, no single
genetic variant could explain these CAD risks. The researchers could not explain
the other 69% risk for greater CAD risk in shorter people.
According to the Journal
of the American Medical Association, epigenetics is “at the epicenter of modern medicine”. DNA sequences (genes) are
generally independent of lifestyle and environmental factors. However, the
sub-cellular microenvironment contains heritable chemical factors that can
alter genetic controls, thereby influencing disease risk. The overhyping of epigenetic
diets and drugs has been criticized, as has the ambiguity of its definition.
But epigenetics is a tool – a scientific discipline – that might connect
genetic DNA sequences (big data) to the observed risk of disease in populations
(statistics).
On Silicon Valley’s Sand Hill Road, the smart money that
created eBay, Google, Napster and Facebook is backing the premise that life can
be extended by studying big genetic databases, using super-computing analytics
at supra-terabyte levels to uncover the causes of death. As public research funding
stalls, increasingly, private investors and venture capitalists are driving the
biomedical research agenda. If dense data contained within the genome and
epi-genome can be sorted, the cause and effect secrets of the human body may be
reverse-engineered into deeper understandings of the basis for diseases and longevity.
The same technological wizards who engineered social media, secure
online payments and movie streaming are turning their problem solving skills to
the ultimate challenge – prolonging life. What would happen to society, to
humanity, if the 1% of the world’s population controlling 50% of its wealth
could afford the biomedical interventions permitting 150 year lifespans? Along
with Bill and Melinda Gates, 130 billionaires have signed the ‘Giving Pledge’
to donate half of their accumulated trillions of dollars to engineer better
health through advanced biomedical research tied to big data analytics.
These tech billionaires are ushering in another Gilded Age
of philanthropy that could ultimately benefit global health. But to some, these
initiatives appear more suited to preventing the ills of the rich – as Bill
Gates said, “It seems pretty egocentric
while we still have malaria and TB for rich people to fund things so they can
live longer”.
Here’s the rub…
With thousands of genes being sequenced, with untold chemicals
in the epigenetic ooze, and with hundreds of thousands of subjects contributing
their DNA to big databases, the statistical possibilities are almost endless.
Titans who changed the world by harvesting the power of
machines & technology believe that they can also improve the human
condition. Whether it’s Rockefellers or the Gates, the belief in what’s
possible drives investing more powerfully than any damn statistic.
If Mark Twain had enjoyed great longevity, perhaps he’d
opine today that, “There are data, big
data and analytics”.
The Square shares such optimism! You gotta believe in
something, right?
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