Because individual metal concentrat

Because individual metal concentrations
were moderately or highly correlated in preliminary
analyses [Pearson correlation coefficient
range, 0.13–0.66; see Supplemental Material,
Table S1 (http://dx.doi.org/10.1289/
ehp.1206187)], we calculated an overall estimate
of association with metal exposure by
pooling ORs estimated for individual metals
(antimony, arsenic, cadmium, chromium, lead,
manganese, mercury, nickel), using a randomeffects
meta-analysis with the SAS Mixed procedure
(Higgins et al. 2009). Additionally, we
estimated associations between ASD and an
overall measure of metal exposure that was
derived by summing the quintile category score
(1–5, with 1 representing the lowest quintile)
for each metal (antimony, arsenic, cadmium,
chromium, lead, manganese, mercury, nickel)
to create an overall score with values ranging
from 8 to 40.
We examined the association of the
covariates with the overall metals metric and
Roberts et al.
980 volume 121 | number 8 | August 2013 • Environmental Health Perspectives
conducted additional analyses using this metric,
examining the effects of state of residence,
family income, smoking during pregnancy,
HAP model year and urbanicity on the association
between this metals metric and ASD
[see Supplemental Material, Methods (http://
dx.doi.org/10.1289/ehp.1206187)]. All models
were adjusted for HAP year, tract median
income, tract percent college educated,
maternal age at birth, child’s year of birth,
and maternal parents’ education. We did not
adjust for family income or spouse/partner’s
education in main analyses because they were
measured after the child’s birth for most children,
and the child’s ASD status may have
affected income and educational attainment.
Additionally, we did not adjust for smoking
during pregnancy in the main analyses because
65 cases were missing smoking data (Table 1).
To investigate further whether one or
two pollutants were driving the association
between correlated pollutants and ASD, we
conducted analyses with diesel, lead, manganese,
mercury, methylene chloride, and
nickel—the pollutants most strongly associated
with ASD based on tests of highest versus
lowest quintile as well as linear trend—in a
single model.

ผลลัพธ์ (อังกฤษ) 2:

Because individual Metal concentrations
were moderately or highly correlated in Preliminary
analyzes [Pearson correlation coefficient
Range, 0.13-0.66; See Supplemental Material,
Table S1 (Http://dx.doi.org/10.1289/
Ehp.1206187)], we calculated an overall Estimate
of association with Metal exposure by
pooling ORs estimated for individual Metals
(Antimony, Arsenic, cadmium, chromium. , Lead,
manganese, Mercury, Nickel), using a Randomeffects
Meta-Analysis with the SAS Mixed procedure
(Higgins et al. 2009). Additionally, we
estimated Associations between ASD and an
overall measure of Metal exposure that was
derived by the quintile Summing Category Score
(1-5, with 1 representing the lowest quintile)
for each Metal (Antimony, Arsenic, cadmium,
chromium, Lead, manganese. , Mercury, Nickel)
to create an overall Score with values ​​ranging
from 8 to 40.
We examined the association of the
covariates with the overall METRIC Metals and
Roberts et al.
980 volume 121 |. number 8 | August two thousand and thirteen • Environmental Health Perspectives
conducted additional analyzes using this METRIC,
examining the effects of State of Residence,
Family income, smoking during Pregnancy,
HAP Model year and urbanicity on the association
between this Metals METRIC and ASD
[See Supplemental Material, Methods (HTTP. : //
Dx.doi.org/10.1289/ehp.1206187)]. All models
were adjusted for HAP year, Tract Median
income, Tract PERCENT College educated,
maternal Age at birth, Child's year of birth,
maternal and parents' Education. We did not
Adjust for Family income or Spouse / Partner's
Education in Main analyzes because they were
measured after the Child's birth for Most children,
and the Child's ASD Status May have
AFFECTED income and educational Attainment.
Additionally, we did not Adjust for smoking
during Pregnancy. in the Main analyzes because
65 Cases were Missing smoking Data (Table 1).
To Investigate further whether one or
Two pollutants were Driving the association
between correlated pollutants and ASD, we
conducted analyzes with Diesel, Lead, manganese,
Mercury, methylene chloride, and.
Nickel-the pollutants Most strongly associated
with ASD based on tests of highest Versus
lowest quintile as well as Trend-linear in a
single Model.