ArticlePDF Available

Abstract and Figures

Mounting evidence indicates that early-life exposure to particulate air pollutants pose threats to children’s cognitive development, but studies about the neurotoxic effects associated with exposures during adolescence remain unclear. We examined whether exposure to ambient fine particles (PM2.5) at residential locations affects intelligence quotient (IQ) during pre-/early- adolescence (ages 9–11) and emerging adulthood (ages 18–20) in a demographically-diverse population (N = 1,360) residing in Southern California. Increased ambient PM2.5 levels were associated with decreased IQ scores. This association was more evident for Performance IQ (PIQ), but less for Verbal IQ, assessed by the Wechsler Abbreviated Scale of Intelligence. For each inter-quartile (7.73 μg/m³) increase in one-year PM2.5 preceding each assessment, the average PIQ score decreased by 3.08 points (95% confidence interval = [-6.04, -0.12]) accounting for within-family/within-individual correlations, demographic characteristics, family socioeconomic status (SES), parents’ cognitive abilities, neighborhood characteristics, and other spatial confounders. The adverse effect was 150% greater in low SES families and 89% stronger in males, compared to their counterparts. Better understanding of the social disparities and sexual dimorphism in the adverse PM2.5–IQ effects may help elucidate the underlying mechanisms and shed light on prevention strategies.
Content may be subject to copyright.
Socioeconomic disparities and sexual
dimorphism in neurotoxic effects of ambient
fine particles on youth IQ: A longitudinal
Pan Wang
*, Catherine Tuvblad
, Diana Younan
, Meredith Franklin
, Fred Lurmann
Jun Wu
, Laura A. Baker
, Jiu-Chiuan Chen
1Center for Health Policy Research, University of California Los Angeles, Los Angeles, United States of
America, 2Department of Psychology, University of Southern California, Los Angeles, United States of
America, 3School of Law, Psychology and Social Work, O
¨rebro University, O
¨rebro, Sweden, 4Department
of Preventive Medicine, University of Southern California, Los Angeles, United States of America, 5Sonoma
Technology, Inc., Petaluma, California, United States of America, 6Program in Public Health, University of
California Irvine, Irvine, United States of America
These authors contributed equally to this work.
Mounting evidence indicates that early-life exposure to particulate air pollutants pose threats
to children’s cognitive development, but studies about the neurotoxic effects associated with
exposures during adolescence remain unclear. We examined whether exposure to ambient
fine particles (PM
) at residential locations affects intelligence quotient (IQ) during pre-/
early- adolescence (ages 9–11) and emerging adulthood (ages 18–20) in a demographically-
diverse population (N = 1,360) residing in Southern California. Increased ambient PM
els were associated with decreased IQ scores. This association was more evident for Perfor-
mance IQ (PIQ), but less for Verbal IQ, assessed by the Wechsler Abbreviated Scale of
Intelligence. For each inter-quartile (7.73 μg/m
) increase in one-year PM
preceding each
assessment, the average PIQ score decreased by 3.08 points (95% confidence interval =
[-6.04, -0.12]) accounting for within-family/within-individual correlations, demographic char-
acteristics, family socioeconomic status (SES), parents’ cognitive abilities, neighborhood
characteristics, and other spatial confounders. The adverse effect was 150% greater in low
SES families and 89% stronger in males, compared to their counterparts. Better understand-
ing of the social disparities and sexual dimorphism in the adverse PM
–IQ effects may help
elucidate the underlying mechanisms and shed light on prevention strategies.
Intelligence is a broad collection of cognitive abilities including reasoning, problem solving,
attention, memory, knowledge, planning, and creativity sub-served by different parts of the
brain. Intelligence quotient (IQ), a global measure of intellectual development, is an important
PLOS ONE | December 5, 2017 1 / 15
Citation: Wang P, Tuvblad C, Younan D, Franklin
M, Lurmann F, Wu J, et al. (2017) Socioeconomic
disparities and sexual dimorphism in neurotoxic
effects of ambient fine particles on youth IQ: A
longitudinal analysis. PLoS ONE 12(12): e0188731.
Editor: Tim S. Nawrot, Universiteit Hasselt,
Received: January 9, 2017
Accepted: November 13, 2017
Published: December 5, 2017
Copyright: ©2017 Wang et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: This work was supported by the National
Institute of Environmental Health Sciences (grant
R21 ES022369 to JC),
The USC RFAB Twin Study is funded by the
National Institute of Mental Health (grant R01
MH058354 to LB), The
funders had no role in study design, data collection
and analysis, decision to publish, or preparation of
determinant of national wealth and economic growth [1]. It is estimated that a single point
change of IQ could bring a gain of $55 billion to $65 billion (in year 2000 dollars) for a single
birth cohort of US population [2]. At the individual level, childhood IQ is a powerful predictor
of later-life socioeconomic success [3]. Although the brain size has reached 90% of adult size
by age 5 [4], development of efficient brain structure and networks in early childhood contin-
ues into adolescence. There is an increasing recognition that IQ can change significantly dur-
ing adolescence [5].
Adolescence, defined by the World Health Organization [6] as the period from ages 10 to
19 (after childhood and before adulthood), is a transition stage characterized by many signifi-
cant biological and social changes. Human growth during adolescence is greatly influenced by
changes in hormone production and neuroendocrine response [7] with the beginning of
reproductive lifespan, while the developing brain is undergoing further remolding of gray mat-
ter (e.g., cortical thinning) [8] and white matter (e.g., continuing myelination of axons) [9].
The growing adolescents start to disengage from their parents and exert more autonomous
control on their own decisions and actions. These biological and social changes not only sug-
gest that plasticity in IQ development continues with interactions among brain, behavior, and
social context, but that adolescent brains are also vulnerable to environmental insults from var-
ious neurotoxins. As the brain network matures by the end of adolescence [4,10], IQ is
expected to remain relatively stable until the advent of aging during late adulthood.
Environment in general can explain up to 50% of individual difference in IQ, with its result-
ing influence depending on socioeconomic context [11] and age [12]. Research on environ-
ment-mediated IQ effect is thus important as such knowledge may help identify potentially
modifiable factors and develop timely intervention to reduce disparities in cognitive develop-
ment. While there has been extensive research on IQ development and social adversities in the
family and school environments [1315], influences of physical environments are understudied.
Exposure to ambient particulate air pollutants, including PM
(particulate matter [PM]
with aerodynamic diameter <2.5 μm), has emerged as a novel environmental neurotoxin
affecting brain development in children [16]. The hypothesized link of child intellectual devel-
opment with early-life PM exposures has been examined in several birth cohorts [1727],
including four based in the US and three from Poland, China, and Italy. Although most of the
reported findings generally showed a negative association between PM exposure and IQ in
children, each of these birth cohort studies included only one-time assessment on intellectual
development. One small longitudinal study [28] compared children living in highly-polluted
Mexico City (n = 20) and the control group (n = 10) from a clean-air area (matched on age
and socioeconomic status), and reported in their post-hoc analyses the difference in IQ at
baseline disappeared after one year of follow-up when the matched cohort became 8 years old.
Therefore, it remains unclear whether PM exposure could still exert adverse effect on intellec-
tual development during adolescence. The primary aim of our current study was to examine
the adverse effect of PM
on IQ, using longitudinal data spanning a 12-year period. Because
previous studies have been underpowered to assess the potential heterogeneity in the reported
associations, our secondary aim was to evaluate whether the putative neurotoxic adverse effect
on intellectual development during adolescence, if any, could vary by sex and family socioeco-
nomic status (SES) based on a relatively large sample (N = 1360).
Materials and methods
Participants were drawn from the University of Southern California (USC) Risk Factors for
Antisocial Behavior (RFAB) twin study. RFAB is a prospective longitudinal study of the
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 2 / 15
the manuscript. The author FL worked at Sonoma
Technology Inc. while engaged in this research.
Sonoma provided support in the form of salaries
for author FL, but did not have any additional role
in the study design, data collection and analysis,
decision to publish, or preparation of the
manuscript. The specific role of FL is articulated in
the ‘author contributions’ section.
Competing interests: Fred Lurmann is employed
by Sonoma Technology, Inc. There are no patents,
products in development or marketed products to
declare. This does not alter our adherence to all the
PLOS ONE policies on sharing data and materials,
as detailed online in the guide for authors. There is
no conflict of interest associated with the
publication of this manuscript, as disclosed by all
contributing authors.
interplay of genetic, environmental, social, and biological factors on the development of anti-
social behavior from pre-adolescence to early adulthood. Participating families were recruited
from communities in Los Angeles and surrounding counties, with the resulting sample repre-
sentative of the socio-economically-diverse multi-ethnic population residing in the greater Los
Angeles area [29]. To date, five waves of data have been collected from 780 twin pairs
(N = 1,569 in total including triplets). Study protocols were approved by the USC Institutional
Review Board. Informed consents were obtained from all participants (after reaching adult-
hood) or their parents/guardians (during pre-adolescence).
The current study utilized IQ data collected from the RFAB cohort during pre-/early- ado-
lescence (aged 9–11) and emerging adulthood (aged 18–20). Our analytic sample was limited
to participants with at least one valid IQ score and a corresponding estimate of air pollution
exposure, plus complete data on major sociodemographic characteristics (including age, gen-
der, race/ethnicity and family SES). A total of 1,360 subjects (from 687 families) were retained
in the main analyses, including 810 tested during pre-/early- adolescence only, 170 during
emerging adulthood only, and 380 at both age periods. These three groups did not differ in the
distributions by sex, race/ethnicity, or family SES (S1 Table). Subjects tested with higher IQ
scores at baseline were more likely to participate in the follow-up, but their IQ scores were no
different from those only tested during the emerging adulthood. The PM
exposure 1-year
before the baseline testing was slightly lower among subjects tested twice, as compared to
those not participating in the second testing (20.28 ±2.82 vs. 20.59 ±2.53; p= .06), but there
was no statistically significant difference in the PM
exposure estimate at the follow-up
between the two groups assessed during emerging adulthood.
Assessment of IQ
IQ was measured using the Wechsler Abbreviated Scale of Intelligence (WASI) [30]. The
WASI provides a quick and reliable assessment of an individual’s verbal, nonverbal, and gen-
eral cognitive functioning. The WASI yields two standardized scores: Verbal IQ and Perfor-
mance IQ. Verbal IQ (VIQ) is based on subtests Vocabulary and Similarities, whereas
Performance IQ (PIQ) is based on subtests Block Design and Matrices. Correlations between
PIQ and VIQ ranged from 0.48 (pre-/early- adolescence) to 0.56 (emerging adulthood) in the
current study. The six-month test-retest reliability (n = 60) was satisfactory for both PIQ
(r= 0.79) and VIQ (r= 0.78).
Estimation of particulate matter exposure
Residential location data and geocoding. Residential addresses for RFAB families were
prospectively collected through self-reports every 2 to 3 years. Addresses were geocoded using
services of the USC Spatial Sciences Institute, which successfully matched residences by exact
parcel locations or specific street segments for 98.6% of participating families. The remaining
addresses were checked for correctness using Google Earth and thereafter geocoded.
Spatiotemporal modeling for PM
.Daily PM
(PM with aerodynamic
diameters <2.5μm) concentrations were obtained from U.S. EPA Technology Transfer Net-
work for the years 2000 to 2014. A spatiotemporal model based on the measured PM
centrations was constructed (with 10-fold cross-validation R
= 0.74–0.79) to estimate
monthly average PM
concentrations for each subject’s geocoded residential location (see
section B in S1 Appendix for more details). A time series of monthly PM
concentrations for
the 2000–2014 period was constructed and monthly estimates were aggregated to represent
exposure 1-, 2-, and 3-years preceding each IQ assessment.
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 3 / 15
Relevant covariates
To control for potential confounding, four groups of covariates were examined: (A) age, gen-
der, race/ethnicity, family SES, and parents’ cognitive abilities; (B) parent-reported neighbor-
hood quality, neighborhood SES (nSES), traffic density and neighborhood greenspace; (C)
CALINE4-estimated total annual nitrogen oxides (NO
) and temperature/humidity; (D) par-
ent-level risk factors (operationalized as maternal smoking during pregnancy and parental
perceived stress). Covariates (A) and (B) were considered as the most relevant confounders as
they were known to predict IQ and also likely influence where people chose to reside (and thus
their exposure to ambient PM
). More details about the selection and measurement of covari-
ates are available in section C of S1 Appendix.
Statistical analyses
Three-level mixed-effects models regressing IQ scores (Full-Scale IQ, VIQ and PIQ separately)
at each assessment on the corresponding PM
exposures and accounting for both within-
family (random intercepts and slopes of PM
effects by families) and within-individual (ran-
dom intercepts by individual) covariance were constructed as the base models. These models
were then adjusted for two sets of covariates incrementally: (1) individual and family charac-
teristics—age (as a continuous variable or dichotomized as pre-/early- adolescence vs. emerg-
ing adulthood), sex, race/ethnicity, family SES, and parental cognitive abilities; and (2)
neighborhood characteristics—nSES, neighborhood greenspace (1000m radius buffer, 1-year
preceding test), traffic density (300m radius buffer), and parent-reported neighborhood qual-
ity. We conducted further sensitivity analyses by adding the following covariates to the fully
adjusted models: ambient temperature and humidity (1-year preceding); total annual NO
and parental risk factors.
Three separate pre-planned moderation analyses were conducted to examine whether the
putative PM
effects on IQ varied by age (pre-/early- adolescence vs. emerging adulthood),
sex, and SES levels (continuous), based on the interaction term between exposure and the
putative moderator, each entering the fully adjusted model one by one. All the analyses were
implemented using SAS 9.4.
Descriptive statistics
Participants’ IQ scores were on average 101.62 (VIQ, SD = 17.93) and 100.25 (PIQ,
SD = 17.98) during pre-/early- adolescence (9.59 ±0.58 years); 104.47 (VIQ, SD = 16.01) and
102.71 (PIQ, SD = 16.01) during emerging adulthood (19.44 ±1.07 years). About 99% of par-
ticipants during pre-/early- adolescence and 78% during emerging adulthood were exposed to
(1-year preceding the IQ assessment) levels exceeding the EPA annual standard (12ug/
Population characteristics by quartiles of PM
(Table 1) and Full-Scale IQ (Table 2) at the
study baseline (i.e., the first valid IQ assessment) were examined. The decrease of quartiles of
exposure across age reflected the higher ambient PM
levels in earlier years of testing.
Compared to their counterparts, those with relatively higher PM
exposures were mostly His-
panics and Blacks, from lower quality neighborhoods (characterized by lower nSES, lower
greenness, more negative perception of neighborhood quality and higher annual NOx), resid-
ing in locations with higher temperature and relative humidity, and children whose parents
reported maternal smoking during pregnancy, displayed poorer cognitive abilities, and per-
ceived more stress. On the other hand, children with lower IQ score at baseline were more
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 4 / 15
likely to be Hispanics, Black, and mixed racial/ethnicities; grow up in lower SES households;
have parents perceiving more stress, smoking during pregnancy and demonstrating lower cog-
nitive abilities; and reside in locations with lower neighborhood qualities and higher relative
humidity. For population characteristics by quartiles of VIQ and PIQ, please refer to S2 and S3
Main-effect of PM
on IQ scores
In the base models, higher one-year average PM
predicted lower scores in the full-scale IQ,
VIQ, and PIQ (Table 3). Although PM
exposures were still negatively associated with full-
scale IQ and VIQ in the adjusted analyses, none of these associations reached statistical signifi-
cance. However, the observed adverse PM
effects on PIQ were evident in the adjusted mod-
els. For each inter-quartile (7.73 μg/m
) increase in 1-year PM
, the average PIQ score
Table 1. Population characteristics in relation to the overall
exposure 1-year prior to IQ assessment.
Population Characteristics at
Quartile of PM
2.14–16.08 16.09–18.67 18.68–21.13 21.14–25.36
Median = 13.55 Median = 17.56 Median = 20.16 Median = 22.76
1360 (N = 339) (N = 341) (N = 340) (N = 340) p-value
Age 1360 16.18 ±3.12 12.76 ±2.56 10.11 ±1.73 9.63 ±0.62 <0.0001
Gender 0.0970
Male 690 169 (24.49%) 192 (27.83%) 169 (24.49%) 160 (23.19%)
Female 670 170 (25.37%) 149 (22.24%) 171 (25.52%) 180 (26.87%)
Ethnicity <0.0001
Caucasian 378 147 (38.89%) 83 (21.96%) 80 (21.16%) 68 (17.99%)
Hispanic 504 81 (16.07%) 128 (25.40%) 129 (25.6%) 166 (32.94%)
Black 188 31 (16.49%) 46 (24.47%) 57 (30.32%) 54 (28.72%)
Asian 58 12 (20.69%) 21 (36.21%) 17 (29.31%) 8 (13.79%)
Other or Mixed 232 68 (29.31%) 63 (27.16%) 57 (24.57%) 44 (18.97%)
Household socioeconomic status 1360 45.35 ±11.21 42.22 ±11.19 41.80 ±12.03 39.70 ±11.07 <0.0001
Neighborhood socioeconomic status 1360 0.31 ±0.93 -0.10 ±0.90 -0.07 ±1.07 -0.39 ±0.85 <0.0001
Neighborhood quality
1344 26.18 ±9.09 26.68 ±9.41 28.97 ±10.70 29.52 ±11.85 <0.0001
Maternal smoking during pregnancy 0.0037
No 1216 309 (25.41%) 312 (25.66%) 288 (23.68%) 307 (25.25%)
Yes 84 16 (19.05%) 13 (15.48%) 34 (40.48%) 21 (25.00%)
Parental WJ Score–Letter Word 1099 59.96 ±9.88 54.23 ±7.43 52.49 ±5.81 54.07 ±6.78 <0.0001
Parental WJ Score–Word Attack 1099 25.52 ±5.30 23.08 ±5.14 23.11 ±4.74 22.82 ±5.16 <0.0001
Parental Stress 1346 30.52 ±8.14 31.88 ±8.40 32.94 ±8.54 32.99 ±8.25 0.0002
NDVI 1-year prior in 1000m area 1360 0.33 ±0.08 0.33 ±0.07 0.32 ±0.09 0.30 ±0.07 <0.0001
Traffic density in 300m area 1360 73.95 ±146.78 90.6 ±138.17 87.38 ±139.30 84.37 ±127.64 <0.0001
Temperature 1-year prior (˚C) 1360 17.25 ±0.81 17.50 ±0.68 17.42 ±0.79 17.58 ±0.56 <0.0001
Relative humidity 1-year prior (%) 1360 58.85 ±7.60 61.08 ±6.08 63.49 ±5.95 62.85 ±4.22 <0.0001
Total annual NOx (ppb) 1360 18.70 ±19.02 31.30 ±20.86 34.88 ±22.69 33.94 ±18.92 <0.0001
. Overall exposure defined as the individual-level average of 1-year exposure estimated prior to each IQ assessment
. Baseline referred to the first valid assessment of IQ (either Wave 1 or Wave 5 in this study).
. Total number of subjects decrease slightly due to missing values.
. P-value from the ANOVA test comparing means of continuous variables or Pearson χ
test comparing the distribution of VIQ across categorical variables
across the quartile of outcome variable.
. Higher score represented a more negative perception of neighborhood quality.
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 5 / 15
decreased by 3.08 points (95% CI = [-6.04, -0.12]) in the mixed-effect model accounting for
within-family/within-individual correlations, demographic characteristics, family SES,
parents’ cognitive abilities, perceived neighborhood quality, nSES, traffic density, and measure
of greenspace (Adjusted Model-II). The observed adverse PM
-PIQ effect remained robust in
sensitivity analyses with further statistical adjustment for temperature and humidity (Sensitiv-
ity Model-1), total annual NO
(Sensitivity Model-II), and parental stress and maternal smok-
ing during pregnancy (Sensitivity Model-III).
Additional analyses on 2- and 3-year average PM
exposure effects on IQ (full-scale; VIQ;
PIQ) revealed a fairly similar pattern of associations across different temporal scales of expo-
sure (S1 Fig). Post-hoc analyses were also conducted to explore the possibility of differential
impact of PM
on each component score of PIQ (Block Design; Matrix Reasoning) or VIQ
(Vocabulary; Similarities). We found the negative PM
-PIQ association primarily reflected
the adverse effect on Matrix Reasoning. Interestingly, although the negative PM2.5-VIQ asso-
ciations were not statistically significant (S1 Fig), we found evidence for adverse effects on
Table 2. Population characteristics at baseline in relation to full-scale IQ.
Population Characteristics N
Quartile of IQ
45–92 93–103 104–114 115–149
Median = 83 Median = 99 Median = 109 Median = 121
1360 (N = 351) (N = 327) (N = 345) (N = 337) p-value
Age 1360 10.73 ±3.01 10.55 ±2.85 10.83 ±3.27 10.91 ±3.40 0.4707
Gender 0.5498
Male 690 176 (25.51%) 164 (23.77%) 168 (24.35%) 182 (26.38%)
Female 670 175 (26.12%) 163 (24.33%) 177 (26.42%) 155 (23.13%)
Ethnicity <0.0001
Caucasian 378 28 (7.41%) 58 (15.34%) 106 (28.04%) 186 (49.21%)
Hispanic 504 182 (36.11%) 156 (30.95%) 110 (21.83%) 56 (11.11%)
Black 188 73 (38.83%) 49 (26.06%) 40 (21.28%) 26 (13.83%)
Asian 58 11 (18.97%) 16 (27.59%) 20 (34.48%) 11 (18.97%)
Other or Mixed 232 57 (24.57%) 48 (20.69%) 69 (29.74%) 58 (25.00%)
Household socioeconomic status 1360 36.65 ±9.70 39.14 ±11.31 44.43 ±10.73 48.94 ±10.36 <0.0001
Neighborhood socioeconomic status 1360 -0.54 ±0.59 -0.16 ±0.90 0.07 ±0.91 0.39 ±1.17 <0.0001
Neighborhood quality
1344 30.01 ±12.02 27.58 ±10.67 27.4 ±9.39 26.35 ±8.96 <0.0001
Maternal smoking during pregnancy <0.0001
No 1216 296 (24.34%) 295 (24.26%) 308 (25.33%) 317 (26.07%)
Yes 84 34 (40.48%) 21 (25.00%) 21 (25.00%) 8 (9.52%)
Parental WJ Score–Letter Word 1099 53.34 ±8.23 54.21 ±8.06 55.51 ±7.68 57.33 ±7.67 <0.0001
Parental WJ Score–Word Attack 1099 22.31 ±6.30 22.75 ±5.09 24.02 ±4.57 25.43 ±3.81 <0.0001
Parental Stress 1346 33.70 ±8.57 32.60 ±8.05 31.95 ±8.72 30.07 ±7.76 <0.0001
NDVI 1-year prior in 1000m area 1360 0.29 ±0.06 0.31 ±0.08 0.33 ±0.08 0.35 ±0.09 <0.0001
Traffic density in 300m area 1360 90.85 ±146.9 88.42 ±148.94 86.99 ±142.76 69.87 ±109.65 0.1801
Temperature 1-year prior (˚C) 1360 17.41 ±0.70 17.47 ±0.72 17.46 ±0.77 17.41 ±0.72 0.6110
Relative humidity 1-year prior (%) 1360 62.62 ±5.92 61.64 ±6.27 61.23 ±6.65 60.76 ±6.37 0.0010
Total annual NOx (ppb) 1360 32.80 ±21.83 31.25 ±22.38 28.74 ±21.58 26.01 ±19.21 0.0002
. Total number of subjects decrease slightly due to missing values.
. P-value from the ANOVA test comparing means of continuous variables or Pearson χ
test comparing the distribution of VIQ across categorical variables
across the quartile of outcome variable.
. Higher score represented a more negative perception of neighborhood quality.
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 6 / 15
VIQ Similarities present for both 1-y (p= .04) and 2-year (p= .02) PM
exposures (S1 Fig).
Annual NO
exposure also predicted lower IQ scores in the crude analyses (S4 Table), but
their associations were largely abolished in the adjusted analyses (S4 Table).
Moderation roles of socio-demographic characteristics
Results of our moderation analyses showed that the adverse PM
effects on PIQ were not uni-
form across socio-demographic characteristics (upper panel, Fig 1). Sex and family SES both
significantly modified the association between PM
and PIQ score (interaction p<.01 for
both moderators), with exposure conferring 150% stronger influence in males (β= -4.68, 95%
CI = [-7.90, -1.47]) than in females (β= -1.87, 95% CI = [-4.89, 1.16]); and 89% stronger in low
SES families (β= -3.83, 95% CI = [-6.98, -0.69]) than in high SES families (β= -2.03, 95% CI =
[-6.12, 2.36]). Although the adverse PM
-PIQ effect (β= -3.27; 95% CI = [-6.44, -0.10]) at age
9–11 was 74% greater than the corresponding estimate (β= -1.88; 95% CI = [-6.12, 2.36]) dur-
ing emerging adulthood, this observed difference by age did not reach statistical significance
(interaction p= .49).
The moderation analyses of VIQ did not reveal remarkable findings, except for a statisti-
cally significant interaction (p= .03) between gender and PM
(lower panel, Fig 1). Our
results suggested that the PM
-VIQ effect might be qualitatively different between males (β=
-2.16; 95% CI = [-5.5, 1.18]) and females (β= 0.78, 95% CI = [-2.37, 3.93]), albeit an overlap
between these two CIs (please refer to Knezevik [31] for an explanation of why a significant
difference could have overlapping CIs).
To our knowledge, this is the first longitudinal study examining the effects of ambient air pol-
lutants on IQ spanning two different developmental stages: pre-/early-adolescence (aged
9–11) and emerging adulthood (aged 18–20). We found strong evidence for a decreased PIQ
score with higher exposure to ambient PM
estimated at residential locations, even after
Table 3. Associations between PM
and IQ measures.
Models N
Full-Scale IQ
β(95% CI)
β(95% CI)
β(95% CI)
Crude Analysis 1360 -2.46 (-3.48, -1.44)*-1.66 (-2.76, -0.56)*-2.14 (-3.16, -1.12)*
Adjusted Model I
1093 -1.93 (-4.75, 0.89) -1.37 (-4.39, 1.65) -2.91 (-5.83, 0.01)
Adjusted Model II
1085 -2.00 (-4.84, 0.84) -1.42 (-4.48, 1.64) -3.08 (-6.04, -0.12)*
Sensitivity Analyses
Sensitivity Model I
1085 -1.84 (-4.86, 1.18) -1.14 (-4.37, 2.09) -3.50 (-6.62, -0.38)*
Sensitivity Model II
1085 -2.08 (-4.96, 0.80) -1.76 (-4.84, 1.32) -3.01 (-5.99, -0.03)*
Sensitivity Model III
1042 -2.05 (-4.87, 0.77) -1.13 (-4.17, 1.91) -3.66 (-6.62, -0.70)*
. Total number of participants differed because of missing values.
. Estimate reflected the change in each IQ score and the resulting 95% confidence interval per each inter-quartile range (IQR) increase in PM
. Adjusted for age, gender, ethnicity, family SES and parents’ cognitive abilities.
. Adjusted Model I + neighborhood SES, self-reported neighborhood quality, traffic density (300m) and neighborhood greenness (1000m, 1-year
. Adjusted Model II + temperature and relative humidity 1-year prior to test.
. Adjusted Model II + total annual NO
. Adjusted Model II + parental stress and maternal smoking during pregnancy.
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 7 / 15
adjusting for socio-demographic factors, spatial characteristics of residential neighborhoods,
and parents’ cognitive abilities. The corresponding associations with VIQ were less evident.
The adverse PM
-PIQ effect was much greater in low SES families and in males, indicative of
socioeconomic disparities and sexual dimorphism in the developmental neurotoxicity of
The observation of stronger adverse PM
effects on IQ among RFAB participants growing
up in low SES families offers a useful view-scope to unify the findings reported in the extant lit-
erature (11 studies from 7 birth cohorts with individual-level exposure data) on PM-IQ associ-
ations (Table D in S1 Appendix). For those 4 studies conducted outside the US [19,20,23,25],
differences in PM characterization and primary exposure source may explain the discrepancies
in reported associations. Of the 7 US-based studies, 6 reported a statistically significant associa-
tion between early-life exposure to PM and low performance of IQ testing in children. These
included 4 studies based in the Columbia Center for Children’s Environmental Health Birth
Cohort, which included children of minority (Black or Dominican-American) women primar-
ily with low SES (74% families with annual family income <$20,000) and residing in a com-
munity where traffic and residential heating were major exposure sources [18,21,24,26]. The
other 3 studies, despite all having been based in the greater Boston area and employing the
same approaches to estimating residential exposure at birth locations, yielded very different
results. In the Project Viva [22], neither black carbon nor PM
exposure predicted lower IQ
Fig 1. Plot of regression coefficients and 95% confidenceintervals for the association between PM
1-year prior to test
and the IQ scores, moderation by age, sex, and family socioeconomic status (RFAB Cohort 2000–2014). The gray
reference band in each IQ subscale represented the 95% CI of the final-adjusted main effect of PM
on that IQ score. Significant
moderation was highlighted in yellow.
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 8 / 15
in children (with an average age of 8) of relatively well-off (73% with annual family income
>$70,000) and well-educated parents (68% maternal/ 63% paternal education college). For
the other two studies including mothers primarily of minorities and/or with limited educa-
tional attainment (69–82% with maternal education high school), PM
was associated with
low full-scale IQ in boys of school age (6.5 ±0.98 years) [27], whereas black carbon exposure
predicted low Matrices score on the Kaufman Brief Intelligence Test at 8–11 years of age [17].
All these study findings point to the importance of population social context [32] for designing
epidemiological studies and interpreting data on developmental neurotoxicity of ambient air
Our finding of socioeconomic disparities in the adverse PM
-PIQ effect has important
implications for future research on the environmental neurosciences in neurodevelopmental
toxicity of particulate air pollutants. First, PM
exposure and socioeconomic adversities may
have converged on common pathways with resulting exacerbated neurotoxicity, although the
exact models for their respective mechanistic actions remain unclear. Possible brain regions
and structures with shared vulnerability may include hippocampus [33,34], prefrontal cortex
[35,36], and cerebral white matter [24,37]. Second, high-SES families may provide their chil-
dren with more exposure to advantageous experiences (e.g., early-life educational resources),
which could partly off-set the brain damage from PM
exposure. Third, although our analyses
accounted for parental cognitive abilities, low-SES families may not be able to engage in activi-
ties with parental nurturance critical for cognitive development. Fourth, growing up in low
SES families indicates the possibility of concurrent exposures to other psychosocial and envi-
ronmental stressors (e.g., violence exposure, early onset of alcohol use) adversely affecting IQ
development. Better understanding of the causes of socioeconomic disparities in PM neuro-
toxicity will not only shed light on the mechanistic pathways, but also help identify more sus-
ceptible populations who can benefit the greatest from environmental regulation, social
policies (e.g., reducing family poverty; early education program), or family interventions (e.g.,
parental caring behaviors).
Although PIQ and VIQ were moderately correlated, the adverse PM
-IQ effect was statis-
tically significant for PIQ only (primarily affecting the Matrix Reasoning component). This
divergence may reflect a more detrimental impact of PM on fluid cognitive abilities. Fluid
intelligence (Gf) refers to the capabilities to reason and solve novel problems, in contrast to
crystallized intelligence (Gc), another factor of intelligence concerning acquired knowledge,
skills and experiences [38,39]. This classical distinction laid the theoretical foundation for the
development of PIQ and VIQ. It is interesting to note that our ad hoc analyses (S1 Fig) also
showed that increased PM
(1- and 2-year average) exposure was associated with decreased
scores in the VIQ subtest Similarity, a measure intended for Gc but actually tapping into Gf
(likely more than the PIQ subtest Block Design, a spatial visualization task) as it relies upon
the ability to abstract common patterns beyond the knowledge of words and their meanings
[40]. Because Gf is more reliant on and sensitive to lesions to frontal lobe than Gc [4145], the
differential PM
effect on fluid intelligence implies possible damage to frontal brain net-
works, which was supported by the emerging data from neurotoxicological and neuroimaging
studies. For instance, persistent glial activation in frontal cortex was demonstrated in mouse
models with early-life exposure to concentrated ambient ultrafine particles [46]. In utero expo-
sure to a low concentration of diesel exhaust also altered the neurochemical monoamine
metabolism in prefrontal cortex [47]. In a birth cohort study based in Rotterdam, the Nether-
lands, early-life exposure to PM
was associated with cortical thinning in the frontal lobe at
age 9 [48].
Two recent studies have reported adverse PM effects on IQ [27] and working memory [49]
assessed in school age were stronger in boys than girls, although none of the exposure
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 9 / 15
interaction with sex was statistically significant. Our study showed that the adverse PM
effects on both PIQ and VIQ scores assessed during early adolescence and emerging adulthood
were stronger in males than females (interaction p-value <.05; Fig 1), despite female RFAB
participants being more likely to reside in locations with higher PM
and 4
quartiles in
Table 1). Multiple biological differences may help explain the observed differences between
males and females in observed adverse PM
-IQ effects in the current study. Neurotoxicolo-
gists have documented sexually dimorphic neurobehavioral responses to various environmen-
tal chemicals (e.g., dioxin, bisphenol-A), a phenomenon often inferred as an indicator for
exposure-induced endocrine-disrupting effects on the brain, largely through interference with
the actions of gonadal hormones [50]. Animal studies support the neuroendocrine disruption
with inhaled exposure to particles [51,52], but the mechanisms underlying sexual dimorphism
in neurotoxicity may also involve neurobiological pathways with exposure interacting with
sex-linked genes [53]. Although earlier studies did not show clear evidence for sex differences
in general intelligence [54], new findings support the presence of cognitive sex differences
depending on task characteristics and contextual experience [55]. However, studies relating
pubertal sex hormones to cognitive abilities in adolescents have yielded mixed results [56,57].
Nonetheless, our findings give strong rationale for future studies to investigate whether sexual
dimorphism is also present in other neurodevelopmental and behavioral effects of ambient air
pollutants. Better understanding of the neurobiological processes underlying the sexual dimor-
phism in the PM
-IQ effect may inform better sex-sensitive intervention strategies to reduce
harmful environmental exposures to optimize the brain-behavioral health for both men and
Our moderation analyses revealed no statistical interaction of exposure effect by age group,
despite the fact that the adverse PM
-PIQ effect was 74% stronger in pre-/early-adolescence
than in emerging adulthood. Behavior genetic research has reported that environmental con-
tribution to IQ variation decreases across age [12,58]. As neural structure and network
approach maturation by the end of adolescence [4,10], IQ of young adults may be less subject
to environmental influences. Previous studies have shown that the use of neurotoxic agents,
such as alcohol and other drugs, posed more threats to memory and memory-related brain
function in adolescents than adults [59]. However, given a relatively small sample (n = 510)
assessed during emerging adulthood, our results must be viewed with caution, as they did not
necessarily mean that the neurotoxic threats of ambient air pollutants disappeared once into
adulthood. Hippocampal damage with cognitive impairments was previously documented in
mice with long-term inhaled exposure to concentrated PM
starting in youth [33]. Future
studies with larger samples could help clarify this important uncertainty in the adverse PM
IQ effect during the transition into young adults.
The strengths of our study included its base in Southern California with wide exposure con-
trast, sampled from a population with rich diversity in race/ethnicity, sex and family SES, and
the inclusion of repeated IQ assessment for longitudinal analyses. This unique sample and pro-
spective longitudinal design provided adequate power to investigate heterogeneity in the
PM-IQ associations across age, sex, and SES. Nonetheless, there are several limitations that
should be considered. First, we caution the interpretation of selective PM
-PIQ effect.
Because our assessment of IQ was based on the WASI (an abbreviated Wechsler intelligence
scale, rather than the full scale), some significant domains (e.g., working memory; processing
speed) presumably sensitive to PM
neurotoxicity were not captured in our analyses. Second,
although we were able to conduct longitudinal analyses, the inference of our results was based
on the statistical assumption of data missing at random given the unbalanced data structure
with repeated measures. Third, we were not able to study prenatal exposure effects, because
extensive monitoring of PM
data were not available until after 1999, while the birth years of
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 10 / 15
the cohort ranged from 1990–1995. The relative contribution to adverse PM
-IQ effects by
exposure in early life versus adolescence needs to be investigated further. Fourth, our analyses
only included the estimate of PM
mass, and we did not study the specific neurotoxicity of
constituents (e.g., metals; organic chemicals). Fifth, while PM
estimates based on spa-
tiotemporal interpolation of monitored concentrations were statistically cross-validated, there
are expected non-differential measurement errors in such estimates, which would likely have
attenuated the observed associations.
In this first longitudinal study with repeated cognitive assessment, we found lower PIQ
scores in youth living in locations with higher exposure to ambient PM
, with stronger
adverse effects observed in low SES families and in males. Better understanding of the socio-
economic disparities and sexual dimorphism in neurotoxic effects of PM
on intellectual
development may help elucidate the underlying mechanisms and shed light for targeted and
effective interventions.
Supporting information
S1 Data. Microsoft excel file of IQ scores, PM
and relevant covariates for the 1360 sub-
jects across pre-/early- adolescence and emerging adulthood.
S1 Fig. Plot of regression coefficients and 95% confidence intervals for the associations
between PM
(1-, 2- and 3-year preceding test) and subscales of IQ from the final-
adjusted model.
S1 File. Appendix. A. Map of Residential Locations during pre-/early- adolescence and emerg-
ing adulthood; B. Temporal-spatial Modeling of PM
Exposure; C. Relevant Covariates; D.
Summary Table of Air Pollution and IQ Studies.
S1 Table. Descriptive statistics of major demographic characteristics, PM
1-year preced-
ing and IQ scores of three sub-cohorts.
S2 Table. Population Characteristics at Baseline in Relation to Levels of Verbal IQ.
S3 Table. Population Characteristics at Baseline in Relation to Levels of Performance IQ.
S4 Table. Associations between total annual NOx and subscales of IQ.
This study used data from the USC-RFAB twin study. We thank the USC research staff for
their assistance in collecting data, and subjects for their participation.
Author Contributions
Conceptualization: Laura A. Baker, Jiu-Chiuan Chen.
Data curation: Pan Wang, Catherine Tuvblad, Diana Younan, Meredith Franklin, Fred
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 11 / 15
Formal analysis: Pan Wang, Catherine Tuvblad.
Funding acquisition: Laura A. Baker, Jiu-Chiuan Chen.
Investigation: Laura A. Baker, Jiu-Chiuan Chen.
Methodology: Pan Wang, Catherine Tuvblad, Jun Wu, Jiu-Chiuan Chen.
Project administration: Pan Wang, Catherine Tuvblad.
Resources: Jun Wu.
Software: Diana Younan, Meredith Franklin, Fred Lurmann.
Validation: Pan Wang, Catherine Tuvblad, Diana Younan, Jiu-Chiuan Chen.
Visualization: Pan Wang.
Writing original draft: Pan Wang, Catherine Tuvblad, Diana Younan, Jiu-Chiuan Chen.
Writing review & editing: Pan Wang, Catherine Tuvblad, Diana Younan, Meredith Frank-
lin, Fred Lurmann, Jun Wu, Laura A. Baker, Jiu-Chiuan Chen.
1. Lynn R, Vanhanen T. IQ and global inequality: Washington Summit Publishers; 2006.
2. Grosse SD, Matte TD, Schwartz J, Jackson RJ. Economic gains resulting from the reduction in chil-
dren’s exposure to lead in the United States. Environmental Health Perspectives. 2002; 110(6):563.
PMID: 12055046
3. Strenze T. Intelligence and socioeconomic success: A meta-analytic review of longitudinal research.
Intelligence. 2007; 35(5):401–26.
4. Lenroot RK, Giedd JN. Brain development in children and adolescents: insights from anatomical mag-
netic resonance imaging. Neuroscience & Biobehavioral Reviews. 2006; 30(6):718–29.
5. Ramsden S, Richardson FM, Josse G, Thomas MS, Ellis C, Shakeshaft C, et al. Verbal and non-verbal
intelligence changes in the teenage brain. Nature. 2011; 479(7371):113–6.
nature10514 PMID: 22012265
6. WHO. Adolescent Development2011 2016 August.
7. Dahl RE. Adolescent brain development: a period of vulnerabilities and opportunities. Keynote address.
Annals of the New York Academy of Sciences. 2004; 1021(1):1–22.
8. Giorgio A, Watkins K, Chadwick M, James S, Winmill L, Douaud G, et al. Longitudinal changes in grey
and white matter during adolescence. Neuroimage. 2010; 49(1):94–103.
neuroimage.2009.08.003 PMID: 19679191
9. Tamnes CK, Østby Y, Fjell AM, Westlye LT, Due-Tønnessen P, Walhovd KB. Brain maturation in ado-
lescence and young adulthood: regional age-related changes in cortical thickness and white matter vol-
ume and microstructure. Cerebral cortex. 2010; 20(3):534–48.
PMID: 19520764
10. Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, et al. Dynamic mapping of
human cortical development during childhood through early adulthood. Proceedings of the National
Academy of Sciences of the United States of America. 2004; 101(21):8174–9.
pnas.0402680101 PMID: 15148381
11. Turkheimer E, Haley A, Waldron M, D’Onofrio B, Gottesman II. Socioeconomic status modifies heritabil-
ity of IQ in young children. Psychological science. 2003; 14(6):623–8.
7976.2003.psci_1475.x PMID: 14629696
12. Bergen SE, Gardner CO, Kendler KS. Age-related changes in heritability of behavioral phenotypes over
adolescence and young adulthood: a meta-analysis. Twin Research and Human Genetics. 2007; 10
13. McLoyd VC. Socioeconomic disadvantage and child development. American psychologist. 1998; 53
(2):185. PMID: 9491747
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 12 / 15
14. Van Ijzendoorn MH, Juffer F, Poelhuis CWK. Adoption and cognitive development: a meta-analytic
comparison of adopted and nonadopted children’s IQ and school performance. Psychological bulletin.
2005; 131(2):301. PMID: 15740423
15. Christian K, Bachnan H, Morrison F. Schooling and cognitive development. Environmental effects on
cognitive abilities. 2001:287–335.
16. Block ML, Elder A, Auten RL, Bilbo SD, Chen H, Chen J-C, et al. The outdoor air pollution and brain
health workshop. Neurotoxicology. 2012; 33(5):972–84.
PMID: 22981845
17. Suglia SF, Gryparis A, Wright R, Schwartz J, Wright R. Association of black carbon with cognition
among children in a prospective birth cohort study. American journal of epidemiology. 2008; 167
(3):280–6. PMID: 18006900
18. Perera FP, Li Z, Whyatt R, Hoepner L, Wang S, Camann D, et al. Prenatal airborne polycyclic aromatic
hydrocarbon exposure and child IQ at age 5 years. Pediatrics. 2009; 124(2):e195–e202.
10.1542/peds.2008-3506 PMID: 19620194
19. Edwards SC, Jedrychowski W, Butscher M, Camann D, Kieltyka A, Mroz E, et al. Prenatal exposure to
airborne polycyclic aromatic hydrocarbons and children’s intelligence at 5 years of age in a prospective
cohort study in Poland. Environmental health perspectives. 2010; 118(9):1326.
ehp.0901070 PMID: 20406721
20. Perera F, Li T, Lin C, Tang D. Effects of prenatal polycyclic aromatic hydrocarbon exposure and envi-
ronmental tobacco smoke on child IQ in a Chinese cohort. Environmental research. 2012; 114:40–6. PMID: 22386727
21. Lovasi GS, Eldred-Skemp N, Quinn JW, Chang H-w, Rauh VA, Rundle A, et al. Neighborhood social
context and individual polycyclic aromatic hydrocarbon exposures associated with child cognitive test
scores. Journal of child and family studies. 2014; 23(5):785–99.
9731-4 PMID: 24994947
22. Harris MH, Gold DR, Rifas-Shiman SL, Melly SJ, Zanobetti A, Coull BA, et al. Prenatal and childhood
traffic-related pollution exposure and childhood cognition in the project viva cohort (Massachusetts,
USA). Environmental health perspectives. 2015; 123(10):1072.
PMID: 25839914
23. Jedrychowski WA, Perera FP, Camann D, Spengler J, Butscher M, Mroz E, et al. Prenatal exposure to
polycyclic aromatic hydrocarbons and cognitive dysfunction in children. Environmental Science and
Pollution Research. 2015; 22(5):3631–9. PMID: 25253062
24. Peterson BS, Rauh VA, Bansal R, Hao X, Toth Z, Nati G, et al. Effects of prenatal exposure to air pollut-
ants (polycyclic aromatic hydrocarbons) on the development of brain white matter, cognition, and
behavior in later childhood. JAMA psychiatry. 2015; 72(6):531–40.
jamapsychiatry.2015.57 PMID: 25807066
25. Porta D, Narduzzi S, Badaloni C, Bucci S, Cesaroni G, Colelli V, et al. Air pollution and cognitive devel-
opment at age seven in a prospective Italian birth cohort. Epidemiology (Cambridge, Mass). 2015.
26. Vishnevetsky J, Tang D, Chang H-W, Roen EL, Wang Y, Rauh V, et al. Combined effects of prenatal
polycyclic aromatic hydrocarbons and material hardship on child IQ. Neurotoxicology and teratology.
2015; 49:74–80. PMID: 25912623
27. Chiu Y-HM, Hsu H-HL, Coull BA, Bellinger DC, Kloog I, Schwartz J, et al. Prenatal particulate air pollu-
tion and neurodevelopment in urban children: Examining sensitive windows and sex-specific associa-
tions. Environment international. 2016; 87:56–65. PMID:
28. Caldero
´n-Garcidueñas L, Engle R, Mora-Tiscareño A, Styner M, Go
´mez-Garza G, Zhu H, et al. Expo-
sure to severe urban air pollution influences cognitive outcomes, brain volume and systemic inflamma-
tion in clinically healthy children. Brain and cognition. 2011; 77(3):345–55.
bandc.2011.09.006 PMID: 22032805
29. Baker LA, Tuvblad C, Wang P, Gomez K, Bezdjian S, Niv S, et al. The Southern California Twin Regis-
ter at the University of Southern California: III. Twin Research and Human Genetics. 2013; 16(01):336–
30. Wechsler D. Wechsler abbreviated scale of intelligence. San Antonio, TX: Harcourt Assessment;
31. Knezevic A. Overlapping Confidence Intervals and Statistical Significance 2008 [cited 2017 September
32. Bellinger DC, Matthews-Bellinger JA, Kordas K. A developmental perspective on early-life exposure to
neurotoxicants. Environment international. 2016; 94:103–12.
014 PMID: 27235688
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 13 / 15
33. Fonken L, Xu X, Weil ZM, Chen G, Sun Q, Rajagopalan S, et al. Air pollution impairs cognition, pro-
vokes depressive-like behaviors and alters hippocampal cytokine expression and morphology. Molecu-
lar psychiatry. 2011; 16(10):987–95. PMID: 21727897
34. Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, et al. Family income, parental edu-
cation and brain structure in children and adolescents. Nature neuroscience. 2015; 18(5):773–8. https:// PMID: 25821911
35. Block ML, Caldero
´n-Garcidueñas L. Air pollution: mechanisms of neuroinflammation and CNS disease.
Trends in neurosciences. 2009; 32(9):506–16. PMID:
36. Johnson SB, Riis JL, Noble KG. State of the art review: poverty and the developing brain. Pediatrics.
2016; 137(4):peds. 2015–3075.
37. Noble KG, Korgaonkar MS, Grieve SM, Brickman AM. Higher education is an age-independent predic-
tor of white matter integrity and cognitive control in late adolescence. Developmental science. 2013; 16
(5):653–64. PMID: 24033571
38. Cattell RB. Theory of fluid and crystallized intelligence: A critical experiment. Journal of educational psy-
chology. 1963; 54(1):1.
39. Cattell RB. Abilities: Their structure, growth, and action. Oxford, England: Houghton Mifflin; 1971.
40. Kaufman AS, Lichtenberger EO. Assessing adolescent and adult intelligence: John Wiley & Sons;
41. Nisbett RE, Aronson J, Blair C, Dickens W, Flynn J, Halpern DF, et al. Intelligence: new findings and
theoretical developments. American psychologist. 2012; 67(2):130.
PMID: 22233090
42. Duncan J, Burgess P, Emslie H. Fluid intelligence after frontal lobe lesions. Neuropsychologia. 1995; 33
(3):261–8. PMID: 7791994
43. Roca M, Parr A, Thompson R, Woolgar A, Torralva T, Antoun N, et al. Executive function and fluid intel-
ligence after frontal lobe lesions. Brain. 2009; 118(2):234–47.
44. Woolgar A, Parr A, Cusack R, Thompson R, Nimmo-Smith I, Torralva T, et al. Fluid intelligence loss
linked to restricted regions of damage within frontal and parietal cortex. Proceedings of the National
Academy of Sciences. 2010; 107(33):14899–902.
45. Barbey AK, Colom R, Paul EJ, Grafman J. Architecture of fluid intelligence and working memory
revealed by lesion mapping. Brain Structure and Function. 2014; 219(2):485–94.
1007/s00429-013-0512-z PMID: 23392844
46. Allen JL, Liu X, Weston D, Prince L, Oberdo
¨rster G, Finkelstein JN, et al. Developmental exposure to
concentrated ambient ultrafine particulate matter air pollution in mice results in persistent and sex-
dependent behavioral neurotoxicity and glial activation. Toxicological Sciences. 2014; 140(1):160–78. PMID: 24690596
47. Suzuki T, Oshio S, Iwata M, Saburi H, Odagiri T, Udagawa T, et al. In utero exposure to a low concen-
tration of diesel exhaust affects spontaneous locomotor activity and monoaminergic system in male
mice. Particle and fibre toxicology. 2010; 7(1):1.
48. Guxens M, Lubczynska MJ, Muetzel R, Dalmau A, Jaddoe VW, Verhulst FC, et al. Air pollution expo-
sure during pregnancy and brain morphology in young children: a population-based prospective birth
cohort study. Abstracts of the 2016l Epidemiology (ISEE). Research Triangle Park, NC: Environmental
Health Perspectives; 2016.
49. Sunyer J, Esnaola M, Alvarez-Pedrerol M, Forns J, Rivas I, Lo
´pez-Vicente M, et al. Association
between traffic-related air pollution in schools and cognitive development in primary school children: a
prospective cohort study. PLoS Med. 2015; 12(3):e1001792.
1001792 PMID: 25734425
50. Weiss B. Sexually dimorphic nonreproductive behaviors as indicators of endocrine disruption. Environ-
mental health perspectives. 2002; 110(Suppl 3):387.
51. Tsukue N, Yoshida S, Sugawara I, Takeda K. Effect of diesel exhaust on development of fetal reproduc-
tive function in ICR female mice. Journal of health science. 2004; 50(2):174–80.
52. Sirivelu MP, MohanKumar SM, Wagner JG, Harkema JR, MohanKumar PS. Activation of the stress
axis and neurochemical alterations in specific brain areas by concentrated ambient particle exposure
with concomitant allergic airway disease. Environmental health perspectives. 2006:870–4. https://doi.
org/10.1289/ehp.8619 PMID: 16759987
53. Davies W, Wilkinson LS. It is not all hormones: alternative explanations for sexual differentiation of the
brain. Brain research. 2006; 1126(1):36–45. PMID:
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 14 / 15
54. Halpern DF, LaMay ML. The Smarter Sex: A Critical Review of Sex Differences in Intelligence. Educa-
tional Psychology Review. 2000; 12(2):229–46.
55. Miller DI, Halpern DF. The new science of cognitive sex differences. Trends in cognitive sciences. 2014;
18(1):37–45. PMID: 24246136
56. Herlitz A, Reuterskiold L, Loven J, Thilers PP, Rehnman J. Cognitive sex differences are not magnified
as a function of age, sex hormones, or puberty development during early adolescence. Dev Neuropsy-
chol. 2013; 38(3):167–79. PMID: 23573795.
57. Vuoksimaa E, Kaprio J, Eriksson CJ, Rose RJ. Pubertal testosterone predicts mental rotation perfor-
mance of young adult males. Psychoneuroendocrinology. 2012; 37(11):1791–800.
1016/j.psyneuen.2012.03.013 PMID: 22520299
58. Hoekstra RA, Bartels M, Boomsma DI. Longitudinal genetic study of verbal and nonverbal IQ from early
childhood to young adulthood. Learning and Individual Differences. 2007; 17(2):97–114.
59. White AM, Swartzwelder HS. Age-related effects of alcohol on memory and memory-related brain func-
tion in adolescents and adults. Recent developments in alcoholism: Springer; 2005. p. 161–76. PMID:
PM2.5 and youth IQ
PLOS ONE | December 5, 2017 15 / 15
... Both prenatal (Chiu et al., 2016;Girardi et al., 2021;Lertxundi et al., 2019;Loftus et al., 2019;Ni et al., 2022) and postnatal (Binter et al., 2022;Ni et al., 2022;Wang et al., 2017) chronic exposures to PM 2.5 or PM 10 have been linked with lower total intellectual quotient (IQ) and various subscales related to verbal, memory, reasoning or attention skills in school-age children or adolescents. Long considered to be solely a marker of exposure to traffic-related air pollution, several studies now also highlight the intrinsic neurotoxicity of NO 2 . ...
... Of note, significant sensitive windows were observed for postnatal exposure to PM 2.5 at 2-3-year and General, Non-verbal abilities among females in sensitivity analyses. Such exposure assessed at school 2-3 years before cognitive tests has been linked with decreasing working memory in 11-years old Spanish children (Forns et al., 2017) while postnatal exposure measured at home 1-2 years before cognitive tests was related to diminished performance IQ (through the matrix reasoning subscale) or the verbal IQ similarities subscale among 9-20 years old American (Wang et al., 2017). Using distributed lag models covering both pregnancy and the first seven years of life, Rivas et al. showed deleterious associations between exposure at 6-7 years to PM 2.5 and lower working memory in males, and executive attention assessed in males and females at 8 years (Rivas et al., 2019). ...
Full-text available
Background: Combined effect of both prenatal and early postnatal exposure to ambient air pollution on child cognition has rarely been investigated and sensitive periods of sensitivity are unknown. This study explores the temporal relationship between pre- and postnatal exposure to PM10, PM2.5, NO2 and child cognitive function. Methods: Using validated spatiotemporally resolved exposure models, pre- and postnatal daily PM2.5, PM10 (satellite based, 1 km resolution) and NO2 (chemistry-transport model, 4 km resolution) concentrations at the mother's residence were estimated for 1271 mother-child pairs from the French EDEN and PELAGIE cohorts. Scores representative of children's General, Verbal and Non-Verbal abilities at 5-6 years were constructed based on subscale scores from the WPPSI-III, WISC-IV or NEPSY-II batteries, using confirmatory factor analysis (CFA). Associations of both prenatal (first 35 gestational weeks) and postnatal (60 months after birth) exposure to air pollutants with child cognition were explored using Distributed Lag Non-linear Models adjusted for confounders. Results: Median exposure from conception until the 60th month of life was 19.3 μg/m3 for PM10, 12.4 μg/m3 for PM2.5 and 16.9 μg/m3 for NO2. Increased maternal exposure to both PM10 and PM2.5 between the 5th and the 11th gestational weeks was related to higher General, Verbal and Non-verbal abilities among males. On the contrary, increased maternal exposure to PM10 between the 22nd and 29th gestational weeks was associated with lower General and Non-verbal abilities among males. Similar trends were observed for PM2.5. No significant sensitive exposure windows were detected for postnatal exposure, NO2 or among females. Discussion: These results suggest poorer cognitive development among males at 5-6 years following increased maternal exposure to PM10 during mid-pregnancy. Apparent protective associations observed for early prenatal exposure to PM10 and PM2.5 are unlikely to be causal and might be due to live birth selection bias.
... For example, Peterson and colleagues reported that associations between fine particulate matter (PM 2.5 ) exposure during gestation and brain development were stronger in boys, while associations with polycyclic aromatic hydrocarbons (PAHs) were stronger in girls (Peterson et al., 2022). Differences in estimated PM 2.5 effects between girls and boys have also been reported for studies of behavioral problems in childhood (Chiu et al., 2016;Wang et al., 2017). ...
... In this study, we used cortisol and DHEA in hair as an integrated index of hormone concentrations to indicate exposure to stress and long-term HPA axis function (Dettenborn et al., 2010;Kirschbaum et al., 2009;van Holland et al., 2012). Although many potential effect modifiers are likely to be correlated, previous studies examining modification of the relationship between air pollution and cognitive performance have evaluated one effect modifier at a time (Chiu et al., 2016;Hossain et al., 2011;Loftus et al., 2019;Peterson et al., 2022;Rahman et al., 2022;Wang et al., 2017). To our knowledge, no previous study examined multiple effect modifiers simultaneously to account for the relationships between them (Vanderweele et al., 2019). ...
Full-text available
Background: Air pollution exposure during pregnancy affects children's brain function. Maternal stress and nutrition, socioeconomic status, and the child's sex may modify this relationship. Objective: To identify characteristics of children with the largest increases in full-scale IQ (FSIQ) after their mothers used HEPA filter air cleaners during pregnancy. Methods: In this randomized controlled trial we randomly assigned women to receive 1-2 air cleaners or no air cleaners during pregnancy. We analyzed maternal hair samples for cortisol and dehydroepiandrosterone (DHEA). When the children were 48 months old, we measured FSIQ with the Wechsler Preschool and Primary Scale of Intelligence. We evaluated ten potential modifiers of the intervention-FSIQ relationship using interaction terms in separate regression models. To account for correlations between modifiers, we also used a single regression model containing main effects and intervention x modifier terms for all potential modifiers. Results: Among 242 mother-child dyads with complete data, the intervention was associated with a 2.3-point increase (95% CI: -1.5, 6.0 points) in mean FSIQ. The intervention improved mean FSIQ among children of mothers in the bottom (5.4 points; 95% CI: -0.8, 11.5) and top cortisol tertiles (6.1 points; 95% CI: 0.5, 11.8), but not among those whose mothers were in the middle tertile. The largest between-group difference in the intervention's effect was a 7.5-point (95% CI: -0.7, 15.7) larger increase in mean FSIQ among children whose mothers did not take vitamins than among children whose mothers did take vitamins (interaction p-value = 0.07). We also observed larger benefits among children whose mothers did not complete university, and those with lower hair DHEA concentrations, hair cortisol concentrations outside the middle tertile, or more perceived stress. Conclusion: The benefits of reducing air pollution during pregnancy on brain development may be greatest for mothers who do not take vitamins, experience more stress, or have less education.
... Der Klimawandel geht Hand in Hand mit der Industrialisierung, Urbanisierung und Luftverschmutzung. Luftverschmutzung wirkt schädlich auf die kognitiven Funktionen und kann Aufmerksamkeit, visuokonstruktive Fähigkeiten, Gedächtnis, Rechenleistung, Leseverständnis sowie verbale und nonverbale Intelligenz beeinträchtigen [5][6][7]. Eine wachsende Zahl an Studienbefunden weist außerdem auf einen Zusammenhang zwischen Luftverschmutzung und Risiko für psychische Erkrankungen wie z. B. Depression, Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS) und Schizophrenie hin [8][9][10]. ...
Full-text available
Zusammenfassung Der Klimawandel und die damit häufiger auftretenden Extremwetterereignisse wirken sich direkt negativ auf die psychische Gesundheit aus. Naturkatastrophen gehen insbesondere mit einem Anstieg von Depressionen, Angst- und Traumafolgestörungen einher. Indirekte Folgen des Klimawandels wie Nahrungsmittelknappheit, ökonomische Krisen, gewaltvolle Konflikte und unfreiwillige Migration stellen zusätzlich massive psychische Risiko- und Belastungsfaktoren dar. Klimaangst und Solastalgie, die Trauer um verlorenen Lebensraum, sind neue psychische Syndrome angesichts der existenziellen Bedrohung durch die Klimakrise. Eine nachhaltige Psychiatrie muss sich dementsprechend auf steigenden und veränderten Bedarf einstellen. Psychiatrische Behandlungsprinzipien müssen die Prävention stärker in den Blick nehmen, um das Versorgungssystem insgesamt zu entlasten. Ressourcenverschwendung und CO 2 -Ausstoß im psychiatrischen Behandlungsablauf sowie Infrastruktur müssen wahrgenommen und verhindert werden. Psychiatrische Aus‑, Fort- und Weiterbildungskonzepte sollen um die Thematik des Klimawandels erweitert werden, um Fachkräfte, Betroffene und Öffentlichkeit umfassend zu informieren, zu sensibilisieren und zu klimafreundlichem und gesundheitsförderlichem Verhalten anzuregen. Die Auswirkungen des Klimawandels auf die psychische Gesundheit müssen tiefergehend erforscht werden. Die DGPPN wird Förderer und strebt die Klimaneutralität bis 2030 an. Sie hat sich zu klimaschonenden und energiesparenden Maßnahmen im Bereich der Finanzwirtschaft, in Bezug auf den DGPPN-Kongress sowie die DGPPN-Geschäftsstelle verpflichtet.
... Der Klimawandel geht Hand in Hand mit der Industrialisierung, Urbanisierung und Luftverschmutzung. Luftverschmutzung wirkt schädlich auf die kognitiven Funktionen und kann Aufmerksamkeit, visuo-konstruktive Fähigkeiten, Gedächtnis, Rechenleistung, Leseverständnis sowie verbale und non-verbale Intelligenz beeinträchtigen [5][6][7]. Eine wachsende Zahl an Studienbefunden weist außerdem auf einen Zusammenhang zwischen Luftverschmutzung und Risiko für psychische Erkrankungen wie z. B. Depression, ADHS und Schizophrenie hin [8][9][10]. ...
Full-text available
Children and adolescents are the groups particularly vulnerable to the consequences of the climate crisis. Global warming, extreme weather phenomena, and progressive environmental degradation have an adverse effect on their development. It is up to the adults to make decisions and actions allowing for mitigating the consequences of climate change, opting for an environmentally friendly household management, offering protection and support to the children, as well as explaining the situation to them and shaping their attitudes. That is why the presented research focuses precisely on parents, the specificity of their functioning in the climate crisis compared to childless people. The study included a group of 333 adults, including 67 parents. Self-report methods were used, including questionnaires developed specifically for this project that examined knowledge about the climate and belief in climate myths; as well as the inventories on current and planned pro-ecological activity. The proprietary scale examining climate emotions and the Climate Change Anxiety Scale by Clayton and Karazsia were also used. The relationships between the variables established in the group of parents and the differences between the groups of people who are parents and those who do not have children were analyzed. Based on the results of the study, an attempt was made to analyze the experiences and behaviours of parents in the context of the climate crisis, and a number of guidelines were formulated that can help them in dealing with children so that they experience the climate situation in the least burdensome way possible, while at the same time receiving support from adults, creating habits that are good for the climate and building up the motivation for pro-environmental activity.
Full-text available
Over the past few decades, air pollution and climate change have become major global concerns. In light of this concern about Indian cities, where air pollution and climate change have a significant health impact, this review was conducted. Human health is at risk from the expanding urban areas that experience extreme climate events like high rainfall, extreme temperature, floods, and droughts. Urban residents are experiencing thermal discomfort and a number of health issues as a result of the elevated temperature levels brought on by the intensified heat waves brought on by climate change. The study also looks at the rising levels of air pollution that are higher than what is required for the majority of Indian megacities. The concentrations of PM and aerosols have been investigated, and the potentially harmful effects on human health of particles that enter the respiratory system and are inhaled by humans have also been discussed. Also looked at were the health effects of the COVID-2019 lockdown on Indian cities' air quality. Lastly, the link between urbanization, air pollution, and climate change has been shown because air pollutants like aerosols affect Earth's climate directly (through absorption and scattering) and indirectly (through modifying cloud properties and radiation transfer processes). As a result, the information in this review will act as a starting point for policymakers when it comes to evaluating vulnerable regions and putting into action plans to reduce air pollution. Based on the review, adaptation and mitigation measures can be implemented in Indian cities to mitigate the effects on human health by regularly monitoring air pollution and addressing climate change.
The societal costs of air pollution have historically been measured in terms of premature deaths (including the corresponding values of statistical lives lost), disability-adjusted life years, and medical costs. Emerging research, however, demonstrated potential impacts of air pollution on human capital formation. Extended contact with pollutants such as airborne particulate matter among young persons whose biological systems are still developing can result in pulmonary, neurobehavioral, and birth complications, hindering academic performance as well as skills and knowledge acquisition. Using a dataset that tracks 2014-2015 incomes for 96.2% of Americans born between 1979 and 1983, we assessed the association between childhood exposure to fine particulate matter (PM2.5) and adult earnings outcomes across U.S. Census tracts. After accounting for pertinent economic covariates and regional random effects, our regression models indicate that early-life exposure to PM2.5 is associated with lower predicted income percentiles by mid-adulthood; all else equal, children raised in high pollution tracts (at the 75th percentile of PM2.5) are estimated to have approximately a 0.51 decrease in income percentile relative to children raised in low pollution tracts (at the 25th percentile of PM2.5). For a person earning the median income, this difference corresponds to a $436 lower annual income (in 2015 USD). We estimate that 2014-2015 earnings for the 1978-1983 birth cohort would have been ∼$7.18 billion higher had their childhood exposure met U.S. air quality standards for PM2.5. Stratified models show that the relationship between PM2.5 and diminished earnings is more pronounced for low-income children and for children living in rural environments. These findings raise concerns about long-term environmental and economic justice for children living in areas with poor air quality where air pollution could act as a barrier to intergenerational class equity.
Full-text available
Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM2.5), daily nitrogen dioxide (NO2), and 8-h maximum ozone (O3) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Study℠. Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.
Full-text available
In the United States, >40% of children are either poor or near-poor. As a group, children in poverty are more likely to experience worse health and more developmental delay, lower achievement, and more behavioral and emotional problems than their more advantaged peers; however, there is broad variability in outcomes among children exposed to similar conditions. Building on a robust literature from animal models showing that environmental deprivation or enrichment shapes the brain, there has been increasing interest in understanding how the experience of poverty may shape the brain in humans. In this review, we summarize research on the relationship between socioeconomic status and brain development, focusing on studies published in the last 5 years. Drawing on a conceptual framework informed by animal models, we highlight neural plasticity, epigenetics, material deprivation (eg, cognitive stimulation, nutrient deficiencies), stress (eg, negative parenting behaviors), and environmental toxins as factors that may shape the developing brain. We then summarize the existing evidence for the relationship between child poverty and brain structure and function, focusing on brain areas that support memory, emotion regulation, and higher-order cognitive functioning (ie, hippocampus, amygdala, prefrontal cortex) and regions that support language and literacy (ie, cortical areas of the left hemisphere). We then consider some limitations of the current literature and discuss the implications of neuroscience concepts and methods for interventions in the pediatric medical home.
Full-text available
This meta-analysis of 62 studies (N=17,767 adopted children) examined whether the cognitive development of adopted children differed from that of (a) children who remained in institutional care or in the birth family and (b) their current (environmental) nonadopted siblings or peers. Adopted children scored higher on IQ tests than their nonadopted siblings or peers who stayed behind, and their school performance was better. Adopted children did not differ from their nonadopted environmental peers or siblings in IQ, but their school performance and language abilities lagged behind, and more adopted children developed learning problems. Taken together, the meta-analyses document the positive impact of adoption on the children's cognitive development and their remarkably normal cognitive competence but delayed school performance.
Full-text available
Background: Brain growth and structural organization occurs in stages beginning prenatally. Toxicants may impact neurodevelopment differently dependent upon exposure timing and fetal sex. Objectives: We implemented innovative methodology to identify sensitive windows for the associations between prenatal particulate matter with diameter ≤ 2.5 μm (PM2.5) and children's neurodevelopment. Methods: We assessed 267 full-term urban children's prenatal daily PM2.5 exposure using a validated satellite-based spatio-temporally resolved prediction model. Outcomes included IQ (WISC-IV), attention (omission errors [OEs], commission errors [CEs], hit reaction time [HRT], and HRT standard error [HRT-SE] on the Conners' CPT-II), and memory (general memory [GM] index and its components - verbal [VEM] and visual [VIM] memory, and attention-concentration [AC] indices on the WRAML-2) assessed at age 6.5±0.98 years. To identify the role of exposure timing, we used distributed lag models to examine associations between weekly prenatal PM2.5 exposure and neurodevelopment. Sex-specific associations were also examined. Results: Mothers were primarily minorities (60% Hispanic, 25% black); 69% had ≤12 years of education. Adjusting for maternal age, education, race, and smoking, we found associations between higher PM2.5 levels at 31-38 weeks with lower IQ, at 20-26 weeks gestation with increased OEs, at 32-36 weeks with slower HRT, and at 22-40 weeks with increased HRT-SE among boys, while significant associations were found in memory domains in girls (higher PM2.5 exposure at 18-26 weeks with reduced VIM, at 12-20 weeks with reduced GM). Conclusions: Increased PM2.5 exposure in specific prenatal windows may be associated with poorer function across memory and attention domains with variable associations based on sex. Refined determination of time window- and sex-specific associations may enhance insight into underlying mechanisms and identification of vulnerable subgroups.
Background: Studies of early-life neurotoxicant exposure have not been designed, analyzed, or interpreted in the context of a fully developmental perspective. Objectives: The goal of this paper is to describe the key principles of a developmental perspective and to use examples from the literature to illustrate the relevance of these principles to early-life neurotoxicant exposures. Methods: Four principles are discussed: 1) the effects of early-life neurotoxicant exposure depend on a child's developmental context; 2) deficits caused by early-life exposure initiate developmental cascades that can lead to pathologies that differ from those observed initially; 3) early-life neurotoxicant exposure has intra-familial and intergenerational impacts; 4) the impacts of early-life neurotoxicant exposure influence a child's ability to respond to future insults. The first principle is supported by considerable evidence, but the other three have received much less attention. Discussion: Incorporating a developmental perspective in studies of early-life neurotoxicant exposures requires prospective collection of data on a larger array of covariates than usually considered, using analytical approaches that acknowledge the transactional processes between a child and the environment and the phenomenon of developmental cascades. Conclusion: Consideration of early-life neurotoxicant exposure within a developmental perspective reveals that many issues remain to be explicated if we are to achieve a deep understanding of the societal health burden associated with early-life neurotoxicant exposures.