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RESEARCH ARTICLE
Socioeconomic disparities and sexual
dimorphism in neurotoxic effects of ambient
fine particles on youth IQ: A longitudinal
analysis
Pan Wang
1☯
*, Catherine Tuvblad
2,3☯
, Diana Younan
4
, Meredith Franklin
4
, Fred Lurmann
5
,
Jun Wu
6
, Laura A. Baker
2
, Jiu-Chiuan Chen
4
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.
*panwang@ucla.edu
Abstract
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
2.5
) 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 PM
2.5
lev-
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
3
) increase in one-year PM
2.5
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 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
2.5
–IQ effects may help
elucidate the underlying mechanisms and shed light on prevention strategies.
Introduction
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 | https://doi.org/10.1371/journal.pone.0188731 December 5, 2017 1 / 15
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OPEN ACCESS
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.
https://doi.org/10.1371/journal.pone.0188731
Editor: Tim S. Nawrot, Universiteit Hasselt,
BELGIUM
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
files.
Funding: This work was supported by the National
Institute of Environmental Health Sciences (grant
R21 ES022369 to JC), https://www.niehs.nih.gov/.
The USC RFAB Twin Study is funded by the
National Institute of Mental Health (grant R01
MH058354 to LB), https://www.nimh.nih.gov. 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 [13–15], influences of physical environments are understudied.
Exposure to ambient particulate air pollutants, including PM
2.5
(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 [17–27],
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
2.5
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
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 | https://doi.org/10.1371/journal.pone.0188731 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
2.5
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
2.5
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
2.5
.Daily PM
2.5
(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
2.5
con-
centrations was constructed (with 10-fold cross-validation R
2
= 0.74–0.79) to estimate
monthly average PM
2.5
concentrations for each subject’s geocoded residential location (see
section B in S1 Appendix for more details). A time series of monthly PM
2.5
concentrations for
the 2000–2014 period was constructed and monthly estimates were aggregated to represent
PM
2.5
exposure 1-, 2-, and 3-years preceding each IQ assessment.
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 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
x
) 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
2.5
). 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
2.5
exposures and accounting for both within-
family (random intercepts and slopes of PM
2.5
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
x
;
and parental risk factors.
Three separate pre-planned moderation analyses were conducted to examine whether the
putative PM
2.5
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.
Results
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
PM
2.5
(1-year preceding the IQ assessment) levels exceeding the EPA annual standard (12ug/
m
3
).
Population characteristics by quartiles of PM
2.5
(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
PM
2.5
exposure across age reflected the higher ambient PM
2.5
levels in earlier years of testing.
Compared to their counterparts, those with relatively higher PM
2.5
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 | https://doi.org/10.1371/journal.pone.0188731 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
Tables.
Main-effect of PM
2.5
on IQ scores
In the base models, higher one-year average PM
2.5
predicted lower scores in the full-scale IQ,
VIQ, and PIQ (Table 3). Although PM
2.5
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
2.5
effects on PIQ were evident in the adjusted mod-
els. For each inter-quartile (7.73 μg/m
3
) increase in 1-year PM
2.5
, the average PIQ score
Table 1. Population characteristics in relation to the overall
a
PM
2.5
exposure 1-year prior to IQ assessment.
Population Characteristics at
Baseline
b
N
c
Quartile of PM
2.5
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
d
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
e
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
a
. Overall exposure defined as the individual-level average of 1-year exposure estimated prior to each IQ assessment
b
. Baseline referred to the first valid assessment of IQ (either Wave 1 or Wave 5 in this study).
c
. Total number of subjects decrease slightly due to missing values.
d
. P-value from the ANOVA test comparing means of continuous variables or Pearson χ
2
test comparing the distribution of VIQ across categorical variables
across the quartile of outcome variable.
e
. Higher score represented a more negative perception of neighborhood quality.
https://doi.org/10.1371/journal.pone.0188731.t001
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 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
2.5
-PIQ effect remained robust in
sensitivity analyses with further statistical adjustment for temperature and humidity (Sensitiv-
ity Model-1), total annual NO
x
(Sensitivity Model-II), and parental stress and maternal smok-
ing during pregnancy (Sensitivity Model-III).
Additional analyses on 2- and 3-year average PM
2.5
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
2.5
on each component score of PIQ (Block Design; Matrix Reasoning) or VIQ
(Vocabulary; Similarities). We found the negative PM
2.5
-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
a
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
b
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
c
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
a
. Total number of subjects decrease slightly due to missing values.
b
. P-value from the ANOVA test comparing means of continuous variables or Pearson χ
2
test comparing the distribution of VIQ across categorical variables
across the quartile of outcome variable.
c
. Higher score represented a more negative perception of neighborhood quality.
https://doi.org/10.1371/journal.pone.0188731.t002
PM2.5 and youth IQ
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VIQ Similarities present for both 1-y (p= .04) and 2-year (p= .02) PM
2.5
exposures (S1 Fig).
Annual NO
x
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
2.5
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
2.5
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
2.5
-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
2.5
(lower panel, Fig 1). Our
results suggested that the PM
2.5
-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).
Discussion
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
2.5
estimated at residential locations, even after
Table 3. Associations between PM
2.5
and IQ measures.
Models N
a
Full-Scale IQ
β(95% CI)
b
VIQ
β(95% CI)
b
PIQ
β(95% CI)
b
Crude Analysis 1360 -2.46 (-3.48, -1.44)*-1.66 (-2.76, -0.56)*-2.14 (-3.16, -1.12)*
Adjusted Model I
c
1093 -1.93 (-4.75, 0.89) -1.37 (-4.39, 1.65) -2.91 (-5.83, 0.01)
Adjusted Model II
d
1085 -2.00 (-4.84, 0.84) -1.42 (-4.48, 1.64) -3.08 (-6.04, -0.12)*
Sensitivity Analyses
Sensitivity Model I
e
1085 -1.84 (-4.86, 1.18) -1.14 (-4.37, 2.09) -3.50 (-6.62, -0.38)*
Sensitivity Model II
f
1085 -2.08 (-4.96, 0.80) -1.76 (-4.84, 1.32) -3.01 (-5.99, -0.03)*
Sensitivity Model III
g
1042 -2.05 (-4.87, 0.77) -1.13 (-4.17, 1.91) -3.66 (-6.62, -0.70)*
*P<.05
a
. Total number of participants differed because of missing values.
b
. Estimate reflected the change in each IQ score and the resulting 95% confidence interval per each inter-quartile range (IQR) increase in PM
2.5
.
c
. Adjusted for age, gender, ethnicity, family SES and parents’ cognitive abilities.
d
. Adjusted Model I + neighborhood SES, self-reported neighborhood quality, traffic density (300m) and neighborhood greenness (1000m, 1-year
preceding).
e
. Adjusted Model II + temperature and relative humidity 1-year prior to test.
f
. Adjusted Model II + total annual NO
x
.
g
. Adjusted Model II + parental stress and maternal smoking during pregnancy.
https://doi.org/10.1371/journal.pone.0188731.t003
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 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
2.5
-PIQ effect was much greater in low SES families and in males, indicative of
socioeconomic disparities and sexual dimorphism in the developmental neurotoxicity of
PM
2.5
exposure.
The observation of stronger adverse PM
2.5
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
2.5
exposure predicted lower IQ
Fig 1. Plot of regression coefficients and 95% confidenceintervals for the association between PM
2.5
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
2.5
on that IQ score. Significant
moderation was highlighted in yellow.
https://doi.org/10.1371/journal.pone.0188731.g001
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 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
2.5
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
pollutants.
Our finding of socioeconomic disparities in the adverse PM
2.5
-PIQ effect has important
implications for future research on the environmental neurosciences in neurodevelopmental
toxicity of particulate air pollutants. First, PM
2.5
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
2.5
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
2.5
-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
2.5
(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 [41–45], the
differential PM
2.5
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
2.5
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 | https://doi.org/10.1371/journal.pone.0188731 December 5, 2017 9 / 15
interaction with sex was statistically significant. Our study showed that the adverse PM
2.5
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
2.5
(3
rd
and 4
th
quartiles in
Table 1). Multiple biological differences may help explain the observed differences between
males and females in observed adverse PM
2.5
-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
2.5
-IQ effect may inform better sex-sensitive intervention strategies to reduce
harmful environmental exposures to optimize the brain-behavioral health for both men and
women.
Our moderation analyses revealed no statistical interaction of exposure effect by age group,
despite the fact that the adverse PM
2.5
-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
2.5
starting in youth [33]. Future
studies with larger samples could help clarify this important uncertainty in the adverse PM
2.5
–
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
2.5
-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
2.5
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
2.5
data were not available until after 1999, while the birth years of
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 December 5, 2017 10 / 15
the cohort ranged from 1990–1995. The relative contribution to adverse PM
2.5
-IQ effects by
exposure in early life versus adolescence needs to be investigated further. Fourth, our analyses
only included the estimate of PM
2.5
mass, and we did not study the specific neurotoxicity of
PM
2.5
constituents (e.g., metals; organic chemicals). Fifth, while PM
2.5
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
2.5
, 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
2.5
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
2.5
and relevant covariates for the 1360 sub-
jects across pre-/early- adolescence and emerging adulthood.
(XLS)
S1 Fig. Plot of regression coefficients and 95% confidence intervals for the associations
between PM
2.5
(1-, 2- and 3-year preceding test) and subscales of IQ from the final-
adjusted model.
(TIF)
S1 File. Appendix. A. Map of Residential Locations during pre-/early- adolescence and emerg-
ing adulthood; B. Temporal-spatial Modeling of PM
2.5
Exposure; C. Relevant Covariates; D.
Summary Table of Air Pollution and IQ Studies.
(PDF)
S1 Table. Descriptive statistics of major demographic characteristics, PM
2.5
1-year preced-
ing and IQ scores of three sub-cohorts.
(PDF)
S2 Table. Population Characteristics at Baseline in Relation to Levels of Verbal IQ.
(PDF)
S3 Table. Population Characteristics at Baseline in Relation to Levels of Performance IQ.
(PDF)
S4 Table. Associations between total annual NOx and subscales of IQ.
(PDF)
Acknowledgments
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
Lurmann.
PM2.5 and youth IQ
PLOS ONE | https://doi.org/10.1371/journal.pone.0188731 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.
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