EDITORIAL
“Correlation Does Not Imply Causation”:
Bradford Hill, Causative Inference, and
Obesity-Related Neuropathy
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eripheral neuropathy is one of the
most common neurologic conditions
of late adulthood. Over 5% of those
older than 55 years of age and over 30% of
those older than 80 have probable or definite
neuropathy.1 Neuropathy is a major cause of
morbidity and reduced quality of life (QOL)
due to pain, gait disturbance, foot ulceration,
and amputation, particularly among diabetic
patients. Up to half of patients with neuropathy have diabetes, and about 40% have
idiopathic neuropathy. A number of studies
suggest that prediabetes and metabolic syndrome are risk factors for idiopathic neuropathy,2-4 although there are conflicting
data.5,6 A growing body of evidence suggests
that obesity, even in the absence of diabetes
or prediabetes, is a significant neuropathy
risk factor.7,8
In this issue of Mayo Clinic Proceedings,
Callaghan et al9 provide a compelling addition to this literature. Their objective was to
determine if obesity in the absence of diabetes or prediabetes increases neuropathy
risk and to explore the role of the distribution of obesity across different body regions.
A total of 138 patients with a body mass
index (calculated as weight in kilograms
divided by height in meters squared) of over
35 kg/m2 were recruited from an academic
bariatric surgery clinic and compared with
46 lean controls who did not fulfill any
component of the metabolic syndrome
defined by the National Cholesterol Education Program Adult Treatment Panel III
(NCEP) criteria. Circumference was
measured at the waist (NCEP criteria) and
multiple other locations. Neuropathy was
defined based on the Toronto consensus
criteria for probable neuropathy.10 Neuropathy was also assessed using a variety of
P
other measures including symptom and sign
scores, skin biopsy to measure intraepidermal nerve fiber density, a robust
measure of small-diameter axons, and nerve
conduction studies. Neuropathy-specific,
general, and obesity-related QOL, pain, and
depression were also assessed.
The prevalence of neuropathy was 2.2%
among controls and 20.3% in obese participants. Neuropathy was observed in 12.1% of
obese individuals with normoglycemia
compared with 7.1% of those with prediabetes and 40.8% with diabetes (P.01).
Although body mass index was comparable
between obese participants with and without
neuropathy (46.4 vs 46.6 kg/m2), the NCEP
waist circumference was larger among those
with neuropathy (139.318.2 cm vs
129.118.7 cm; P¼.01). A multivariable
logistic regression including only data from
obese participants revealed that waist
circumference was the only anthropomorphic variable significantly associated with
neuropathy, with an odds ratio of 1.39 (95%
CI, 1.10-1.75). Age, female sex, height, systolic blood pressure, and triglyceride level
were also associated with neuropathy risk.
Intraepidermal nerve fiber density and most
nerve conduction studies were worse in
obese participants with neuropathy. Most
other neuropathy measures were worse in
obese patients with neuropathy than in those
without. Pain and both general and
neuropathy-specific QOL were worse among
those with neuropathy, although depression
and weight-specific QOL were no different.
Obese patients without clinically defined
neuropathy had lower neuropathy-specific
QOL and greater pain, as well as objective
evidence of early neuropathy, including
reduced intraepidermal nerve fiber density
Mayo Clin Proc. n July 2020;95(7):1306-1309 n https://doi.org/10.1016/j.mayocp.2020.05.017
www.mayoclinicproceedings.org n ª 2020 Mayo Foundation for Medical Education and Research
EDITORIAL
and sural sensory amplitude, and subtle
symptoms and signs based on validated
scales.
These results support the hypothesis that
obesity is a neuropathy risk factor independent
of diabetes or prediabetes and that central
obesity in particular increases the risk. Other
metabolic syndrome components, particularly
systolic blood pressure and serum triglyceride
level, were also associated with neuropathy
risk. As the authors point out, there is variability among studies regarding the relative
importance of metabolic syndrome components other than diabetes and obesity. Participants with prediabetes did not have an
increased neuropathy risk relative to normoglycemic obese individuals (7.1% vs 12.1%),
although their risk was higher than normoglycemic lean controls (2.2%).
This article adds to a growing literature
supporting a risk relationship between
obesity and neuropathy. However, whether
obesity causes neuropathy or is merely a risk
factor is an open question. Causal inference
is the process by which a potential causal
relationship exists between an exposure and
a disease. In 1965, Bradford Hill proposed 9
measures by which causality can be
assessed.11 The Hill criteria are the primary
framework used by epidemiologists to assess
causal inference. Applying these criteria to
the article by Callaghan et al9 and the literature it joins is informative:
1. Strength of association. In the modern
era, statistical significance is viewed as
the measure of strength, but effect size
is clearly relevant. Obese participants
had over 9 times the risk for neuropathy than lean individuals. Those with
normoglycemia were 6 times more
likely to have neuropathy. These comparisons are sizable as well as statistically significant.
2. Consistency. This study adds to a list of
others indicating that obesity is related
to neuropathy risk.
3. Specificity. Hill proposed that the more
specific the relationship, the more likely
it was to be causal. For instance, the
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n
prevalence of scrotal cancer (an otherwise rare condition) among chimney
sweeps described by Potts suggested
soot as a causal factor.12 Although
many patients with neuropathy are not
obese, the same can be said of diabetes.
Because axonal injury is a final common
pathway of many disease processes,
demonstrating specificity in neuropathy
casual inference is challenging.
4. Temporality. Exposure to the putative
causative agent must precede the
disease.
5. Biological gradient. Hill proposed that
causal factors should exhibit a doseresponse effect, although most causal
factors are influenced by other variables,
and thus a simple dose-response curve is
uncommon. The data suggesting that
obese patients without neuropathy
have subtle neuropathy features support
the presence of other risk determinants.
One can view the relationship with neuropathy and prediabetes in this context.
When viewed through the lens of biological gradient, the risk relationship between milder degrees of hyperglycemia
and neuropathy supports the view that
neuropathy in prediabetic patients exists
along a biological gradient from
impaired fasting glucose to impaired
glucose tolerance and diabetes (an indisputable cause of neuropathy).
6-7. Biological plausibility and coherence. A
plausible biological mechanism and
coherence in the data from multiple
sources and studies increase the likelihood of causality. The current study
does not address the biological plausibility of obesity as a cause of neuropathy,
but the metabolic and inflammatory
consequences of obesity share much in
common with those observed with diabetes, and the known substantial biological impact of obesity on multiple
systems supports it as a causal contributor.13 The availability of animal models
of nondiabetic obesity that develop neuropathy further support biological plausibility of obesity as a causal factor.14
https://doi.org/10.1016/j.mayocp.2020.05.017
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MAYO CLINIC PROCEEDINGS
8. Experiment. If obesity causes neuropathy, effectively treating it should lower
neuropathy risk. Multiple studies in
patients with prediabetes and metabolic
syndrome suggest that exercise and
diet improve neuropathy measures and
enhance nerve regenerative capacity,
although these studies do not specifically target obesity and not all show significant weight loss.15-17 These findings
have been replicated in animal models.14
Ongoing studies are exploring the
impact of bariatric surgery and medical
weight loss strategies on diabetic and
nondiabetic neuropathy.
9. Analogy. Strong evidence linking a
causative agent with a disease should
support a causal relationship with a
similar agent even if the evidence is
weaker. Diabetes is an accepted cause
of neuropathy. Nondiabetic obesity
shares common downstream mechanisms with diabetes, and similar metabolic risks, such as hypertension and
hypertriglyceridemia, increase neuropathy risk in both settings.
Although there is a strong causal inference argument that obesity causes neuropathy, more data are needed to conclusively
make this determination. In particular,
experimental evidence that interventions
targeting obesity, such as bariatric surgery or
medically induced weight loss, reduce neuropathy risk would be valuable. The observation that subtle findings of early
neuropathy are seen in many obese patients
who don’t have clinically overt neuropathy is
relevant as this is an ideal population in
which to test therapeutics. Several groups
are exploring this question.
For now, neuropathy symptoms and
signs should be sought in obese patients,
and when present, counseling should be
provided regarding the importance of
exercise and diet as part of a comprehensive approach to obesity management. Even
if obesity does cause neuropathy, other
common potential causes should be
excluded in specific patients, as is the case
in diabetes.
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ACKNOWLEDGMENTS
The views expressed in this article are those of the author
and do not necessarily represent those of the National Institutes of Health.
A. Gordon Smith, MD
Department of Neurology
Virginia Commonwealth University
Richmond, VA
Grant Support: This work was supported in part by grants
U01NS095388 and R01DK064814 from the National Institutes of Health.
Potential Competing Interests: The author reports no
competing interests.
Correspondence: Address to A. Gordon Smith, MD,
Department of Neurology, Virginia Commonwealth University, 1101 E Marshall St, PO Box 980599, Richmond, VA
23298-0599
(Gordon.Smith@vcuhealth.org;
Twitter:
@gordonsmithMD).
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