Frontiers in Public Health,
Journal Year:
2023,
Volume and Issue:
11
Published: Sept. 13, 2023
This
study
sought
to
illustrate
whether
urinary
strontium
levels
were
related
developing
chronic
kidney
disease
(CKD)
in
the
United
States
population.A
total
of
5,005
subjects
identified
from
National
Health
and
Nutrition
Examination
Survey
2011-2016.
Survey-weighted
logistic
regression
analysis,
multivariate
linear
restricted
cubic
spline
(RCS)
plots
curve
stratified
analyses
undertaken
explicate
correlation
between
CKD.With
increase
strontium,
incidence
rate
CKD
albumin
creatinine
ratio
(UACR)
gradually
decreased,
estimated
glomerular
filtration
(eGFR)
increased.
After
controlling
all
confounders,
only
fourth
quartile
was
correlated
a
lower
prevalence
(OR:
0.59;
95%
CI,
0.44-0.79)
compared
lowest
quartile.
Multivariate
analysis
showed
that
positively
with
eGFR
but
negatively
UACR.
RCS
suggested
nonlinear
relationship
(P
for
non-linearity
<0.001).
Stratified
indicated
no
significant
difference
among
different
subgroups.Urinary
strongly
low
risk
CKD,
this
association
non-linear
US
population.
International Journal of Environmental Research and Public Health,
Journal Year:
2023,
Volume and Issue:
20(10), P. 5808 - 5808
Published: May 12, 2023
This
study
aims
to
investigate
the
combined
effects
of
per-
and
polyfluoroalkyl
substances
(PFAS)
on
allostatic
load,
an
index
chronic
stress
that
is
linked
several
diseases,
including
cardiovascular
disease
cancer.
Using
data
from
National
Health
Nutrition
Examination
Survey
(NHANES)
2007–2014,
this
examines
relationship
between
six
PFAS
variables
(PFDE,
PFNA,
PFOS,
PFUA,
PFOA,
PFHS)
load
using
Bayesian
Kernel
Machine
Regression
(BKMR)
analysis.
The
also
investigates
impact
individual
exposure
various
exposure-response
relationships,
such
as
univariate,
bivariate,
or
multivariate
models.
analysis
reveals
PFDE,
PFUA
had
most
significant
positive
trend
with
when
it
was
modeled
a
binary
variable,
while
PFNA
continuous
variable.
These
findings
provide
valuable
insight
into
consequences
cumulative
multiple
which
can
help
public
health
practitioners
identify
dangers
associated
potential
select
interest.
In
summary,
highlights
critical
role
in
stress-related
diseases
emphasizes
need
for
effective
strategies
minimize
these
chemicals
reduce
risk
diseases.
It
underscores
importance
considering
assessing
their
human
offers
information
policymakers
regulators
develop
protect
health.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(9), P. e30271 - e30271
Published: April 26, 2024
This
study
aims
to
fill
the
gap
in
our
understanding
of
distribution
and
ecological
risk
oil
grease
(OG)
toxic
heavy
metals
surface
water
Naf
River,
a
major
transportation
route
connecting
Teknaf
Saint
Martin's
Island
Bangladesh.
Altogether,
6
sampling
stations
this
river
were
assessed
for
OG
metal
pollution,
revealing
presence
both
at
each
station.
The
concentration
is
found
ranging
from
3.6
23.6
mg/L
average
8.13
mg/L.
On
other
hand,
contamination
factor
(C
Environmental Health,
Journal Year:
2024,
Volume and Issue:
23(1)
Published: Nov. 22, 2024
Abstract
Background
Previous
studies
on
the
associations
of
per-
and
polyfluoroalkyl
substances
(PFASs)
heavy
metals
with
lipid
profiles
among
adolescents
have
been
scarce.
We
sought
to
investigate
PFASs
blood
levels
in
a
representative
sample
Korean
adolescents.
Methods
Data
from
National
Environmental
Health
Survey
(2018–2020)
were
used.
Concentrations
[perfluorooctanoic
acid
(PFOA),
perfluorooctane
sulfonic
(PFOS),
perfluorohexane
acid,
perfluorononanoic
(PFNA),
perfluorodecanoic
(PFDeA)],
lead,
mercury
measured
serum,
whole
blood,
urine
samples,
respectively.
Linear
regression,
Bayesian
kernel
machine
regression
(BKMR),
k-means
clustering
analyses
employed
evaluate
between
pollutants
levels.
Results
In
linear
analyses,
PFOA
associated
higher
low-density
lipoprotein
cholesterol
(LDL-C)
levels;
PFOS
total
(TC)
PFNA
TC,
LDL-C,
non-high-density
(non-HDL-C)
PFDeA
non-HDL-C,
high-density
TC
non-HDL-C
The
BKMR
analysis
revealed
that
PFAS
metal
mixture
was
LDL-C
(1.8%
increase
at
75th
percentile
all
concentrations
compared
their
median
values,
95%
credible
interval:
0.5,
3.1),
primarily
driven
by
effect
PFDeA.
Compared
individuals
low
pollutant
exposure
cluster
(geometric
mean
PFOA,
PFOS,
PFHxS,
PFNA,
PFDeA,
2.7
μg/L,
6.2
1.6
0.7
0.4
0.8
μg/dL,
0.3
respectively),
those
high
(5.1
10.7
3.7
1.3
0.6
0.9
respectively)
demonstrated
(2.5%
confidence
0.1,
5.0)
analysis.
Conclusion
Due
limitations
this
study,
such
as
its
cross-sectional
design,
these
results
should
be
interpreted
cautiously
confirmed
future
before
drawing
implications
for
public
health
strategies
aimed
promoting
during
adolescence
later
life.
Diseases,
Journal Year:
2023,
Volume and Issue:
11(1), P. 52 - 52
Published: March 22, 2023
Background/Objective:
This
study
aimed
to
investigate
the
effect
of
exposure
per-
and
polyfluoroalkyl
substances
(PFAS),
a
class
organic
compounds
utilized
in
commercial
industrial
applications,
on
allostatic
load
(AL),
measure
chronic
stress.
PFAS,
such
as
perfluorodecanoic
acid
(PFDE),
perfluorononanoic
(PFNA),
perfluorooctane
sulfonic
(PFOS),
perfluoroundecanoic
(PFUA),
perfluorooctanoic
(PFOA),
perfluorohexane
(PFHS),
metals,
mercury
(Hg),
barium
(Ba),
cadmium
(Cd),
cobalt
(Co),
cesium
(Cs),
molybdenum
(Mo),
lead
(Pb),
antimony
(Sb),
thallium
(TI),
tungsten
(W),
uranium
(U)
were
investigated.
research
was
performed
explore
effects
combined
PFAS
metals
AL,
which
may
be
disease
mediator.
Methods:
Data
from
National
Health
Nutrition
Examination
Survey
(NHANES)
2007
2014
used
conduct
this
persons
aged
20
years
older.
A
cumulative
index
10
biomarkers
cardiovascular,
inflammatory,
metabolic
systems
calculate
AL
out
10.
If
overall
≥
3,
an
individual
considered
chronically
stressed
(in
state
AL).
In
order
assess
dose-response
connections
between
mixtures
outcomes
limit
multicollinearity
other
potential
interaction
exposures,
Bayesian
kernel
machine
regression
(BKMR)
used.
Results:
The
most
significant
positive
trend
mixed
metal
revealed
by
cesium,
molybdenum,
PFHS,
PFNA,
(posterior
inclusion
probabilities,
PIP
=
1,
0.854,
0.824,
0.807,
respectively).
Conclusions:
Combined
increases
likelihood
being
AL.
