The
long-term
health
effects
of
fine
particulate
matter
(PM2.5)
on
hypertension
remain
incomprehensive.
We
evaluated
the
relationship
PM2.5
and
its
components
with
incidence
in
middle-aged
elderly
adults.
utilised
data
from
China
Health
Retirement
Longitudinal
Study
collected
between
2011
2018.
obtained
annual
modelled
dataset
Tracking
Air
Pollution
China,
including
black
carbon
(BC),
sulphate
(SO42-),
organic
(OM),
ammonium
(NH4+),
nitrate
(NO3-).
Time-varying
Cox
models
quantile
g-computation
were
employed
to
explore
associations.
Exposure-response
curves
portrayed
investigate
potential
non-linear
effects.
enrolled
7,032
individuals
a
mean
age
57.14
(range:
45-95)
years.
Over
36,997
person-years
follow-up
(average
time:
5.26
years),
3,119
suffered
hypertension.
With
per
interquartile
range
increment,
hazard
ratios
95%
confidence
intervals
(CIs)
(3.82
[95%
CI:
3.48-4.18]),
BC
(4.17
3.54-4.92]),
SO42-
(4.24
3.50-5.12]),
OM
(3.76
3.14-4.50]),
NH4+
(3.20
2.91-3.52]),
NO3-
(1.94
1.77-2.13])
discovered
lag
1
year.
And
mixed
effect
was
18.0%
16.8%-19.2%],
which
mainly
driven
by
(66.0%)
(34.0%).
Approximate
J-shaped
exposure-response
relationships
revealed.
positive
associations
exposure
adults
aged
≥
45
Controlling
emissions
components,
especially
SO42-,
could
alleviate
burden
Atmosphere,
Год журнала:
2025,
Номер
16(3), С. 292 - 292
Опубликована: Фев. 28, 2025
PM2.5
in
air
pollution
poses
a
significant
threat
to
public
health
and
the
ecological
environment.
There
is
an
urgent
need
develop
accurate
prediction
models
support
decision-making
reduce
risks.
This
review
comprehensively
explores
progress
of
concentration
prediction,
covering
bibliometric
trends,
time
series
data
characteristics,
deep
learning
applications,
future
development
directions.
article
obtained
on
2327
journal
articles
published
from
2014
2024
WOS
database.
Bibliometric
analysis
shows
that
research
output
growing
rapidly,
with
China
United
States
playing
leading
role,
recent
increasingly
focusing
data-driven
methods
such
as
learning.
Key
sources
include
ground
monitoring,
meteorological
observations,
remote
sensing,
socioeconomic
activity
data.
Deep
(including
CNN,
RNN,
LSTM,
Transformer)
perform
well
capturing
complex
temporal
dependencies.
With
its
self-attention
mechanism
parallel
processing
capabilities,
Transformer
particularly
outstanding
addressing
challenges
long
sequence
modeling.
Despite
these
advances,
integration,
model
interpretability,
computational
cost
remain.
Emerging
technologies
meta-learning,
graph
neural
networks,
multi-scale
modeling
offer
promising
solutions
while
integrating
into
real-world
applications
smart
city
systems
can
enhance
practical
impact.
provides
informative
guide
for
researchers
novices,
providing
understanding
cutting-edge
methods,
systematic
paths.
It
aims
promote
robust
efficient
contribute
global
management
protection
efforts.
Ecotoxicology and Environmental Safety,
Год журнала:
2025,
Номер
293, С. 118010 - 118010
Опубликована: Март 1, 2025
Few
studies
have
reported
an
association
between
intrahepatic
cholestasis
of
pregnancy
(ICP)
and
preconception
exposure
to
PM2.5
sunlight
duration,
but
there
has
been
no
in-depth
analysis
the
correlation
ICP
different
constituents
PM2.5.
Thus,
we
performed
this
retrospective
among
160,544
pregnant
women
who
delivered
2014
2020,
further
estimate
impact
PM2.5,
as
well
duration
sunlight,
on
via
generalized
linear
models.
During
three
months
prior
conception,
adjusted
odds
ratios
(aORs)
for
were
1.176
(95
%
CI:
1.066,
1.298)
a
10
μg/m3
increase
in
1.080
1.026,
1.138)
1
sulfate
(SO42-),
1.069
1.025,
1.115)
organic
matter
(OM),
1.274
1.049,
1.546)
black
carbon
(BC),
1.213
1.088,
1.353)
1-hour
decrease
duration.
In
addition,
during
period,
increased
(including
SO42-,
OM,
BC)
decreased
interactively
associated
with
ICP.
Moreover,
OM
first
trimester
(aOR=1.043,
95
1.004,
1.083)
BC
both
(aOR=1.201,
1.000,
1.442)
second
(aOR=1.278,
1.048,
1.558)
found
elevate
risk
future,
preparing
conceive
should
avoid
air
pollution,
related
anthropogenic
emissions
be
controlled
prevent
these
associations.
The
long-term
health
effects
of
fine
particulate
matter
(PM2.5)
on
hypertension
remain
incomprehensive.
We
evaluated
the
relationship
PM2.5
and
its
components
with
incidence
in
middle-aged
elderly
adults.
utilised
data
from
China
Health
Retirement
Longitudinal
Study
collected
between
2011
2018.
obtained
annual
modelled
dataset
Tracking
Air
Pollution
China,
including
black
carbon
(BC),
sulphate
(SO42-),
organic
(OM),
ammonium
(NH4+),
nitrate
(NO3-).
Time-varying
Cox
models
quantile
g-computation
were
employed
to
explore
associations.
Exposure-response
curves
portrayed
investigate
potential
non-linear
effects.
enrolled
7,032
individuals
a
mean
age
57.14
(range:
45-95)
years.
Over
36,997
person-years
follow-up
(average
time:
5.26
years),
3,119
suffered
hypertension.
With
per
interquartile
range
increment,
hazard
ratios
95%
confidence
intervals
(CIs)
(3.82
[95%
CI:
3.48-4.18]),
BC
(4.17
3.54-4.92]),
SO42-
(4.24
3.50-5.12]),
OM
(3.76
3.14-4.50]),
NH4+
(3.20
2.91-3.52]),
NO3-
(1.94
1.77-2.13])
discovered
lag
1
year.
And
mixed
effect
was
18.0%
16.8%-19.2%],
which
mainly
driven
by
(66.0%)
(34.0%).
Approximate
J-shaped
exposure-response
relationships
revealed.
positive
associations
exposure
adults
aged
≥
45
Controlling
emissions
components,
especially
SO42-,
could
alleviate
burden
