Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 16, 2024
Abstract
Background
Cardiometabolic
index
(CMI)
is
a
well-promising
indicator
for
predicting
obesity-related
diseases.
Testosterone
decline
and
deficiency
importantly
affect
men's
health,
may
be
associated
with
obesity
excessive
deposition
of
visceral
adipose
tissue.
Therefore,
this
study
intends
to
explore
the
relationship
between
CMI
testosterone.
Methods
The
present
cross-sectional
was
conducted
among
adult
males
complete
data
about
testosterone
in
2013–2016
National
Health
Nutrition
Examination
Survey
(NHANES).
Calculate
CMI:
Triglyceride
(TG)
(mmol/L)/
High-density
lipid-cholesterol
(HDL–C)
(mmol/L)
×
waist-to-height
Ratio
(WHtR).
Multivariable
regression
subgroup
analyses
were
association
Results
We
included
2,209
male
participants
final
analysis.
After
adjusting
confounders,
found
show
negative
correlation
(Minimally
adjusted
model:
β=-10.56,
95%CI:
-12.76,
-8.36,
P
<
0.0001,
fully
β=-0.04
(-4.88,
4.81),
=
0.9882).
Multivariate-adjusted
beta
also
showed
levels
significantly
lower
two
highest
groups
(Q3,
Q4)
compared
lowest
group
(Q1).
In
populations,
affected
by
age,
race,
Education
level,
Hypertension,
smoking
status
(
-interaction༜0.05).
Furthermore,
ROC
curve
analysis
indicated
that
area
under
(0.68
(95%
CI:
(0.65,0.71)
more
significant
than
TyG
(0.67
0.65,0.70).
Conclusion
negatively
related
decreased
likelihood
United
States
adults.
Our
findings
simple
anthropometric
predict
Frontiers in Cardiovascular Medicine,
Journal Year:
2025,
Volume and Issue:
12
Published: May 12, 2025
Background
Although
the
cardiometabolic
index
(CMI)
has
gained
recognition
as
a
new
tool
for
evaluating
metabolic
health,
relationship
between
CMI
and
cardiovascular
disease
(CVD)
remains
unclear.
This
research
sought
to
explore
potential
association
CVD.
Methods
Participants
from
2007–2018
National
Health
Nutrition
Examination
Survey
(NHANES)
were
selected.
Multivariable
logistic
regression
analyses
smooth
curve
fitting
utilized
investigate
this
relationship,
along
with
subgroup
evaluations
interaction
analyses.
Results
study
included
12,837
subjects
prevalence
of
CVD
was
11.83%.
After
full
adjustment,
participants
presenting
an
increase
one
unit
in
Ln-transformed
associated
15%
higher
odds
(OR
=
1.15,
95%
CI:
1.05–1.26).
In
fully
adjusted
model,
individuals
falling
into
highest
quartile
(Quartile
4)
demonstrated
substantially
35%
than
those
lowest
1)
1.35,
1.11–1.66).
addition,
there
no
nonlinear
our
selected
sample.
positive
not
greatly
influenced
by
any
stratifications.
Conclusions
Among
US
adults,
having
levels
is
prevalence.
finding
suggests
that
regular
monitoring
could
enable
physicians
initiate
early
interventions,
potentially
slowing
progression
However,
order
corroborate
findings,
further
prospective
investigations
are
still
required.
Frontiers in Cardiovascular Medicine,
Journal Year:
2024,
Volume and Issue:
11
Published: Sept. 10, 2024
The
risk
of
congestive
heart
failure
(CHF)
is
significantly
affected
by
obesity.
However,
data
on
the
association
between
visceral
obesity
and
CHF
remain
limited.
We
explored
relationship
cardiometabolic
index
(CMI).
Frontiers in Aging Neuroscience,
Journal Year:
2024,
Volume and Issue:
16
Published: Nov. 29, 2024
It
is
crucial
to
identify
biomarkers
that
influence
the
aging
process
and
associated
health
risks,
given
growing
severity
of
global
population
issue.
The
objectives
our
research
were
evaluate
cardiac
metabolic
index
(CMI)
as
a
novel
biomarker
for
identifying
individuals
at
increased
risk
accelerated
biological
assess
its
use
in
guiding
preventive
strategies
aging-related
risks.
Reproductive Biology and Endocrinology,
Journal Year:
2024,
Volume and Issue:
22(1)
Published: Nov. 14, 2024
Obesity
and
adverse
lipid
profile
leads
to
female
infertility.
The
cardiometabolic
index
(CMI)
is
a
promising
indicator
for
predicting
obesity-related
diseases.
correlation
between
CMI
infertility
merits
further
investigation.
data
this
study
were
acquired
from
the
2013–2020
National
Health
Nutrition
Examination
Survey
(NHANES),
with
2333
women
enrolled.
of
each
participant
was
calculated
as
ratio
triglycerides
high-density
lipoprotein
cholesterol
multiplied
by
waist-to-height
ratio.
Weighted
multivariate
logistic
regression
models
used
assess
independent
log-transformed
Subgroup
analyses
carried
out
reliability
findings.
Interaction
tests
employed
determine
whether
variables
affected
interacting
log
CMI.
A
total
participants
aged
18–45
years
enrolled,
274
whom
infertile.
Log
group
significantly
higher
than
that
non-infertility
(P
<
0.001).
After
adjustment
potential
confounders,
at
an
increased
risk
(OR
=
2.411,
95%
CI:
1.416–4.112),
still
consistent
in
subgroups
under
35
Furthermore,
restricted
cubic
spline
analysis
showed
positive
non-linear
relationship
Cardiometabolic
levels
are
positively
correlated
American
females.
Our
demonstrates
predictive
capacity
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 16, 2024
Abstract
Background
Cardiometabolic
index
(CMI)
is
a
well-promising
indicator
for
predicting
obesity-related
diseases.
Testosterone
decline
and
deficiency
importantly
affect
men's
health,
may
be
associated
with
obesity
excessive
deposition
of
visceral
adipose
tissue.
Therefore,
this
study
intends
to
explore
the
relationship
between
CMI
testosterone.
Methods
The
present
cross-sectional
was
conducted
among
adult
males
complete
data
about
testosterone
in
2013–2016
National
Health
Nutrition
Examination
Survey
(NHANES).
Calculate
CMI:
Triglyceride
(TG)
(mmol/L)/
High-density
lipid-cholesterol
(HDL–C)
(mmol/L)
×
waist-to-height
Ratio
(WHtR).
Multivariable
regression
subgroup
analyses
were
association
Results
We
included
2,209
male
participants
final
analysis.
After
adjusting
confounders,
found
show
negative
correlation
(Minimally
adjusted
model:
β=-10.56,
95%CI:
-12.76,
-8.36,
P
<
0.0001,
fully
β=-0.04
(-4.88,
4.81),
=
0.9882).
Multivariate-adjusted
beta
also
showed
levels
significantly
lower
two
highest
groups
(Q3,
Q4)
compared
lowest
group
(Q1).
In
populations,
affected
by
age,
race,
Education
level,
Hypertension,
smoking
status
(
-interaction༜0.05).
Furthermore,
ROC
curve
analysis
indicated
that
area
under
(0.68
(95%
CI:
(0.65,0.71)
more
significant
than
TyG
(0.67
0.65,0.70).
Conclusion
negatively
related
decreased
likelihood
United
States
adults.
Our
findings
simple
anthropometric
predict