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NeuroToxicology 33 (2012) 687–696
Contents lists available at SciVerse ScienceDirect
NeuroToxicology
Tremor, olfactory and motor changes in Italian adolescents exposed to historical
ferro-manganese emission
Roberto G. Lucchini a,b,*, Stefano Guazzetti c, Silvia Zoni a, Filippo Donna a, Stephanie Peter a,
Annalisa Zacco d, Marco Salmistraro d, Elza Bontempi d, Neil J. Zimmerman e, Donald R. Smith f
a
Occupational Health, University of Brescia, Italy
Mount Sinai Medical School, New York, USA
Public Health Service, Reggio Emilia, Italy
d
INSTM and Chemistry for Technologies Laboratory, University of Brescia, Italy
e
School of Health Sciences, Purdue University, USA
f
Microbiology and Environmental Toxicology, University of California, Santa Cruz, USA
b
c
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 9 August 2011
Accepted 11 January 2012
Available online 31 January 2012
Background and objective: Increased prevalence of Parkinsonism was observed in Valcamonica, Italy, a
region impacted by ferroalloy plants emissions containing manganese and other metals for a century
until 2001. The aim of this study was to assess neurobehavioral functions in adolescents from the
impacted region and the reference area of Garda Lake.
Methods: Adolescents age 11–14 years were recruited through the school system for neuro-behavioral
testing. Metals including manganese, lead, iron, zinc, copper were measured in airborne particulate
matter collected with 24-h personal samplers, and in soil, tap water, blood, urine and hair. Independent
variables included parental education and socio-economic status, children’s body mass index, number of
siblings, parity order, smoking and drinking habits.
Results: A total of 311 subjects (49.2% females), residing in either the exposed (n = 154) or the reference
(n = 157) area participated. Average airborne and soil manganese were respectively 49.5 ng/m3 (median
31.4, range 1.24–517) and 958 ppm (median 897, range 465–1729) in the impacted area, and 27.4 ng/m3
(median 24.7, range 5.3–85.9) ng/m3 and 427 ppm (median 409 range 160–734) in the reference area.
Regression models showed significant impairment of motor coordination (Luria-Nebraska test,
p = 0.0005), hand dexterity (Aiming Pursuit test, p = 0.0115) and odor identification (Sniffin’ task,
p = 0.003) associated with soil manganese. Tremor intensity was positively associated with blood
(p = 0.005) and hair (p = 0.01) manganese.
Conclusion: Historical environmental exposure to manganese from ferroalloy emission reflected by the
concentration in soil and the biomarkers was associated with sub-clinical deficits in olfactory and motor
function among adolescents.
ß 2012 Elsevier Inc. All rights reserved.
Keywords:
Neuromotor changes
Children
Airborne particles
Soil
Metals
Manganese
1. Introduction
Early life exposure to metals such as lead (Pb) and manganese
(Mn) has been shown to cause neurotoxic effects of particular
concern in susceptible subgroups like children. While pediatric
exposure to Pb has been extensively studied for cognitive
impairment, the neuro-developmental effect of Mn has been
ascertained only recently. Exposure to Mn in water (Wasserman
et al., 2006; Bouchard et al., 2011) and airborne dust
* Corresponding author at: Department of Experimental and Applied Medicine,
Section of Occupational Health, University of Brescia, P.le Spedali Civili 1, 25123
Brescia, Italy. Tel.: +39 030 3996604; fax: +39 030 3996080.
E-mail addresses: lucchini@med.unibs.it, rlucchin@gmail.com (R.G. Lucchini).
0161-813X/$ – see front matter ß 2012 Elsevier Inc. All rights reserved.
doi:10.1016/j.neuro.2012.01.005
(Riojas-Rodrı́guez et al., 2010; Menezes-Filho et al., 2011) has
been found to be associated with cognitive impairment measured
as reduced IQ. Since Mn neurotoxicity is known for extrapyramidal effects in adults and has been related to early
Parkinsonism (Lucchini et al., 2007), control of motor function
may be impaired also in younger individuals after early life
exposure. Exposure to Mn can occur from various sources via
inhalation and ingestion routes. Recent animal studies have also
suggested that the olfactory uptake of airborne particulates may be
important in brain Mn uptake, since it would circumvent
physiological barriers (e.g., blood–brain barrier) that normally
regulate to some extent brain uptake (Aschner and Dorman, 2006).
Although studies on the uptake of Mn through the human olfactory
system are not available, it is likely that olfactory transport of Mn
plays an important role in human neurotoxicity (Lucchini et al.,
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2012; Aschner et al., 2005), especially when carried by ultrafine
particles (Elder et al., 2006). Mexican children exposed to severe
air pollution have shown deficits of odor identification related to
signs of inflammation in the olfactory bulb (Calderón-Garcidueñas et al., 2010). The province of Brescia, where 1,200,000
inhabitants live in a territory of 4800 km2, ranks as the third
most industrialized province of Italy. The province has a long
history of metallurgic production, with the iron and ferroalloy
industry being especially prevalent in this area. Ferroalloy air
emissions over the past century have increased environmental
levels of various metals in the province, including manganese
(Mn), lead (Pb), iron (Fe), copper (Cu), zinc (Zn), chromium (Cr),
and nickel (Ni) (Zacco et al., 2009). Cross sectional studies
conducted by our group on ferroalloy workers have shown over
the past two decades impairment of motor functions related to
Mn in blood (MnB) (Lucchini et al., 1995) and to cumulative
exposure indices obtained as a time integrated estimate of
average exposure to airborne Mn (Lucchini et al., 1999). An
environmental epidemiological study of non-worker residents of
Brescia also showed an increased prevalence of Parkinsonism
(crude rate 296/100,000, age-sex standardized rate 407/100,000)
compared to national (157.7/100,000) and international (126–
144/100,000) rates. Moreover, the Standardized Morbidity Ratios
(SMR) for Parkinsonism increased further around the sites of
three ferroalloy plants located in Valcamonica, a valley in the
pre-Alps within the province of Brescia (Kruskal–Wallis chisquared 1 df = 17.55, p-value <0.001). The SMRs were positively
associated with Mn levels in outdoor deposited dust (Lucchini
et al., 2007).
In light of these findings, we undertook a cross sectional study
on behavior, cognitive and motor functions among healthy
individuals resident in Valcamonica and in a reference non
industrial area of the province of Brescia, located on the west
shore of the Garda Lake, where concentrations of metals in
deposited dust are significantly lower (Zacco et al., 2009). Different
age groups were targeted by this project, including pregnant
mothers and infants, adolescents, ferroalloy workers, elderly. Here
we report the results on the assessment of motor and neurosensory
functions among the adolescents; the investigation of cognitive
and behavioral functions and in the other age-groups will be
published elsewhere.
2. Methods
2.1. Study sites
The study area includes different sites of the Province of
Brescia, Northern Italy (Fig. 1): Valcamonica, a valley of the preAlps that runs for about 50 miles in the NE-SW direction with an
average width of about 2 miles, and is delimited by mountains of
about 10,000 feet. Winds in the valley average 3 miles/h primarily
in the SW ! NE direction during the day and NE ! SW during the
night, with no seasonal variation. Here three ferroalloy plants
have been operating in the municipalities of Sellero (pop’n 1500)
from 1973 to 1987, Breno (pop’n 5000) from 1921 to 2001, and
Darfo (pop’n 13,200) from 1902 to 1995. A reference group
community with no history of industrial ferroalloy plant activity
was identified in the Garda Lake area of the Province. A fourth
ferroalloy plant started Mn alloy production in the 1970s and is
currently active in the town of Bagnolo Mella, located on the
Padana plains. Estimated levels of Mn in settled dust obtained by
statistical interpolation of previous measures (Zacco et al., 2009),
showed the highest values in the vicinity surrounding the sites of
previously and currently operating ferroalloy plants (Fig. 2).
Results reported in the present study are based on the sites of
Valcamonica and the Garda Lake.
Fig. 1. Location of the study sites.
2.2. Participant enrollment
Children were enrolled through the public school system
according to a community-based participatory approach that
involved the local communities of Valcamonica and Garda Lake.
The aims and methodology of the study were explained through
community meetings and conferences and publicized by the local
media. Teachers, parents and children were informed with ad hoc
meetings and brochures. Subjects who agreed to participate filled
in a screening questionnaire for the evaluation of inclusion and
exclusion criteria. The inclusion criteria included: (i) to be born in
the study area from resident families living in the study area since
the 1970s; (ii) to live in the study area since birth; (iii) to be aged
11–14 years. The exclusion criteria were represented by: (i)
pathological conditions potentially affecting neuro-development,
including neurological, hepatic, metabolic, endocrine and psychiatric diseases; (ii) consumption of medications with known neuropsychological side-effects; (iii) clinically diagnosed motor deficits
of hand and fingers; (iv) clinically diagnosed cognitive impairment
and behavioral manifestations; (v) visual deficits not adequately
corrected. General practitioners physicians and pediatricians of the
study areas were informed about the research aims and methods.
The study design, the information about the study aims and the
forms for informed consent had been reviewed and approved by
the ethical committees of the local Public Health agencies of
Valcamonica and Brescia.
2.3. Study design
The assessment of participant subjects was divided in three
sessions, and carried out on different days over 2 consecutive
weeks. Trained medical doctors and neuro-psychologists conducted the first session within dedicated rooms in the local school
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689
individually but at group level and discussed in local community
meetings.
2.4. Exposure assessment
Fig. 2. Mn levels as percentage of total deposited dust in the province of Brescia,
Italy. Values estimated with Kriging interpolation obtained with thin-plate spline
regression of geo-referenced data (D: sites of ferroalloy plant; Valcamonica:
previously active; Bagnolo Mella: currently active).
at each site; the session included the collection of sociodemographic data, including socio economic status (SES), family
size, parity order, maternal and paternal education level, alcohol
drinking and smoking habits, clinical and residential history with
ad hoc questionnaires, and the administration of a test battery for
neuropsychological, neurosensory and behavioral examination.
Anthropometric data were measured for the calculation of body
mass index (BMI) and a food frequency questionnaire weighted for
portion sizes was administered to estimate the daily oral intake of
Mn. At the end of the neuropsychological assessment, a portable
pump for 24 h collection of PM10 airborne particles was mounted
in the child’s backpack and collection started. The second session
was devoted to the collection of environmental samples including
soil and tap water at the residential household of each participant.
The third session was dedicated to the collection of biological
matrices for the assessment of candidate biomarkers of metal
exposure, including blood, urine, and hair. Blood samples were also
used to assess cell blood count (CBC), iron status, liver and kidney
function. Each individual participant’s data was entered with
anonymized identification codes accessible only to the research
team, and under the responsibility of the study Principal
Investigator (RL). According to an ethical procedure on open
information about the final study outcomes, individual results on
exposure data and hematological parameters were communicated
to each participant in written form with comparison to the
available exposure protective standards and the normative data for
hematological analysis. Since normative data for the neurobehavioral tests were not considered, results were not communicated
Each participant’s house was geo-referenced for spatial
analysis. Inhalation exposure to PM10 (i.e., 50% collection
efficiency for 10 mm aerodynamic diameter particles) airborne
particulate matter was determined using 24 h personal air
monitoring. Airborne particles were collected on commercial
filters (37 mm diameter, PTFE-Teflon) using Personal Environmental Monitors (PEM) connected to a Leland Legacy pump (SKC, Inc.,
Eighty-Four, PA, USA). The PEM air sampler was mounted onto the
student’s backpack front strap, in or near the breathing zone, while
the pump was carried in the backpack. Pumps were pre-calibrated
to a flow rate of 10 L/min, using a soapless piston primary
calibrator (Defender, BIOS, Butler, NJ, USA), with post-sampling
flow rate confirmation. The pumps were run for 24 consecutive
hours with the child’s school backpack either carried by the child or
placed near the child during school or in the room while they were
sleeping. Each child filled a personal diary with complete records of
their activities and time spent in indoor/outdoor locations during
the air-sampling period. Data on atmospheric conditions during
the sampling period were obtained by the online meteorological
system of the local Environmental Protection Office (ARPA
Lombardia). Total PM10 particulate load on the filter was
determined gravimetrically, as well as chemically. Particulate
metal content was determined using total reflection X-ray
fluorescence (TXRF) spectroscopy, according to a methodology
published elsewhere (Borgese et al., 2011, 2012).
Water was sampled from the primary use home tap after a
2 min run at a medium flow rate and examined with TXRF multielemental analysis, that has a lowest detection limit for Mn in
water of 1 mg/L.
The metal content in the soil was analyzed in situ with a
portable X-ray fluorescence (XRF) instrument (Thermo Scientific
Niton, model XL3t) equipped with GPS geo-referencing capability.
The Niton portable XRF analyzes soil for metals by the generation
of an X-ray signal and the instrument interpretation of the energies
of the returning X-ray fluorescence signal from the excitation of
the metal elements in the soil. Sample collection times ranged from
60 to 100 s. Surface soil measurements were collected in both the
impacted and the reference areas as well as in the yards of a select
number of subjects’ homes. At the homes, two to four randomly
spaced readings were taken and averaged. The instrument was
internally calibrated prior to each usage. In addition, a series of soil
standards reference materials (NIST 2780, 2709a) produced by the
U.S. National Institute of Standards and Technology (NIST) were
measured at the beginning of each sampling session with the Niton
XRF. The collected filters for airborne particles were analyzed in
accordance with the patented method PCT/IT2008/000458
(Depero et al., 2009) which allows the filter to be analyzed directly
and non-destructively without any chemical treatment using total
X-ray fluorescence (TXRF) techniques. The TXRF measurements
were performed with the Bruker TXRF system S2 Picofox, air
cooled, Mo tube, Silicon-Drift Detector, with operating values of
50 kV and 1000 mA, using an acquisition time of 600 s. The
absolute concentration of the elements in the filters was evaluated
through calibration with an air particulate standard filter (NIST
SRM 2783).
A Food Frequency Questionnaire (FFQ) was used to estimate
the daily dietary intake of Mn. The questionnaire included specific
food items such as cereals, whole grain products, vegetable
(chard, spinach), beans, lentils, chickpeas, fruit (pineapple,
hazelnut), tea, cacao, coffee, of known higher Mn content
based on the US nutrient database (USDA, 2010). The intake
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was portion-adjusted based on Italian reference data on food
consumption (Leclercq et al., 2009).
2.5. Collection and analysis of exposure biomarkers
Exposure to Mn and Pb was also measured in total blood and
urine. Venous whole blood samples (4 mL) were collected using a
19-gauge butterfly catheter into a Li-Heparin Sarstedt Monovette
Vacutainer. A spot urine sample (50–200 mL) was collected into a
clean, sterile polyethylene container. All samples were stored at
4 8C until analyzed at the laboratory facility of the University of
Brescia. Hematological tests were performed to assess iron
metabolism and liver function. Hair samples were collected from
each subject using stainless steel scissors. Briefly, a 2–3 cm section
of hair proximal to the scalp (100–150 strands, or 20 mg) was
collected from the nape of the neck and stored in polyethylene bags
at room temperature until analyses.
Manganese and Pb measurements in blood and Mn in urine
(MnU) were performed by Zeeman graphite furnace atomic
absorption spectrometry (Varian SpectrAA) in the Industrial
Hygiene laboratory at the University of Brescia, Italy, using
methods previously reported (Apostoli et al., 2000). Levels of
Mn in hair (MnH) were determined by magnetic sector inductively
coupled plasma mass spectrometry (Thermo XR-Thermo Element
XR ICP-MS). Briefly, hair samples (10–50 mg) were cleaned of
exogenous metal contamination as follows: sonication (20 min) in
0.5% Triton, rinsing 5 with Milli-Q ultrapure water, sonication
(10 min) in 1 N trace metal grade nitric acid, rinse with 1 N nitric
acid, and rinsing 3 with Milli-Q water. Clean hair samples were
dried overnight at 60 8C in a HEPA filtered-air clean room.
Subsequently, hair was transferred to pre-weighed 6 mL poly
tubes and digested in 0.5 mL 15.7 N double quartz-distilled nitric
acid at 80 8C for 6 h in a Class-100 HEPA filtered-air hood.
Following digestion, 5 mL Milli-Q water was added to each tube,
and tubes were capped and vortexed. Rhodium and thalium were
added as internal standards, and samples were analyzed for Pb-208
and Tl-205 (low resolution), and Cr-52, Mn-55, Cu-63, and Rh-103
(medium resolution). Metal concentrations were determined by
comparison with certified multi-element standards (Spex Industries). The analytical detection limits for Mn, Pb, Cu, and Cr were
0.0054, 0.0027, 0.027, and 0.0019 ng/mL, respectively, based on
repeated measurements of procedural blanks on four different
analysis days.
2.6. Neuro-psychological testing
The neurobehavioral test battery was designed based on a
review of the tests reported in the Mn literature (Zoni et al., 2007).
Since pre-clinical early signs of neurotoxicity were considered in
the study design, sensitive neurobehavioral tests were selected to
capture exposure-related changes also in the normality range.
Based on the study design and the exclusion criteria adopted,
normative data were not used in the analysis.
Similarly to other studies on manganese neurotoxicity (Zoni
et al., 2007) motor coordination was explored with 5 subtests of the
Luria Nebraska Motor Battery (Golden et al., 1980), a standardized
test battery composed by a total of 11 clinical scales. The test we
administered, each lasting 10 s, were: dominant hand clench, non
dominant hand clench, alternative hand clench, finger-thumb
touching with dominant hand, finger-thumb touching with non
dominant hand. The sum of the scores of these 5 subtests yielded a
final score that represents, therefore, a partial Luria motor score. For
motor coordination we used also a computerized version of Finger
Tapping (Iregren et al., 1996). To assess psychomotor speed we used
the Finger Tapping test, computerized version from the SPES
(Iregren et al., 1996): task of participant is to tap a push-button
alternatively with the dominant and non-dominant hand within
5 min. From the same computerized system we selected also the
Visual Simple Reaction time test for vigilance and psychomotor
response: the reaction time is the time required to respond to the
presence of a visual stimulus represented by a red rectangle
appearing on the computer screen. The subject is asked to press a
button as soon as a stimulus appears on the screen. Hand dexterity
and perceptual speed were assessed with the Pursuit Aiming test
(Fleischman, 1954). For this test, the subject must place a dot with a
pencil inside 2 mm diameter circles as quickly as possible for two
series of 60 s each. Tremor was assessed by the Tremor 7.0 of Danish
Products Developments-DPD (Després et al., 2000). During the test,
the subject holds a stylus for 10 s and the hand vibrations are
recorded and displayed in a time axis plot. The accelerations are
analysed by methods drawn from vibrations measurements. Body
Sway was recorded by a balance plate (SWAY system by DPD), which
produces signals from three sensors to provide a map of the position
of the force center during the test period. This centre is defined as the
center of equilibrium of the three vertical forces, recorded at the
three supports of the sway plate. During the test the subject stands
erect on the sway plate and the change in position of the force center
can be observed in a X–Y coordinate system. The test was repeated in
two conditions of open and closed eyes. To assess odor identification
we used Sniffin’ Sticks-Olfactory Screening 12 test (Burghart
Medical Technology). The subject smells the tips of 12 fiber sticks
filled with different common scents and must identify the odors
from a list of 4 concepts each. The result of the test is the sum of the
correctly identified odors. We selected this test because the smells
are more familiar to the Italian subjects compared to other produced
elsewhere, and also because this test was already successfully used
in children (Hummel et al., 2007).
2.7. Statistical analysis
Preliminary non-parametric statistics (Mann–Whitney and
Kruskal–Wallis) were used to test the null hypothesis that the
observed values were drawn from the same population in the
impacted and reference area. Since air samples and soil measurements were not collected for the entire population we used GIS
Kriging interpolations to obtain values for the missing points and
gain power in the subsequent regression analyses. The median
distance between points with and without direct soil measures was
780 m (20 m–5.37 km), while for the air measures the median
distance was 119 m (range 20 m–1.9 km). Ordinary Kriging is a geostatistical technique used to estimate data at unobserved locations
from the observations at nearby locations and is based on spatial
correlation of the data. Therefore we used a Stratified (by area)
Ordinary Kriging model based on log-transformed Mn levels to
estimate the unobserved individual soil Mn values. Since spatial
correlation of airborne measurements was weak, we used Inverse
Weighted Distance interpolation (Bivand et al., 2008) to estimate the
unobserved air Mn values. Cross-validation was used to assess the
reliability of the Kriging models. To test the hypothesis that Mn
exposure affects motor and sensory functions in children and to
obtain an adjusted estimate of the effect we used multiple (linear
and logistic) regression analysis. Deviations from linearity in the
relationship between exposure measures and covariate and
dependent variables was evaluated comparing the ordinary least
square model (OLS) or the logistic model with a semi-parametric
generalized additive model (GAM) where the choice of the
smoothness of the non-parametric part of the model was driven
by generalized cross validation (Wood, 2006). When linearity could
not be rejected we reduced the model to the simplest OLS (or
logistic) model or we entered the continuous variable parametrically
in the GAM model. We used soil Mn levels as the surrogate of Mn
exposure to the subjects because of the collinearity (concurvity)
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between the air and soil Mn levels. Using only the soil Mn data
resulted in more stable models and no gain in information was
obtained when retaining the air Mn data in the models, as indicated
by Akaike’s information criterion (Venables and Ripley, 2002). We
retained in the regression models all the variables that could have
been related both to the exposure and to the outcome, including age,
gender, SES, family size, parity order, maternal and paternal
education, alcohol and smoking habits, BMI. These variable were
included on an ‘‘a priori’’ basis, even when they showed to be
statistically non significant, in order to obtain an unbiased estimate
of the effect of Mn exposure (Harrell, 2001). All the analyses and
graphics were made with R (R Development Core Team, 2011).
3. Results
3.1. Social-demographics
The study included 311 adolescents from different families and
households, selected from a total of 414 originally enrolled.
Exclusion was due to: not meeting the residence criteria (n = 61);
refusal to participate (n = 22), neurological and psychiatric
diseases (n = 12); incomplete informed consent (n = 5); endocrine
diseases (n = 1); metabolic disease (n = 1); total parenteral
nutrition (n = 1). Participants resided in Valcamonica (n = 154)
and in the Garda Lake area (n = 157). According to the three sites of
previous ferroalloy operations, the subjects from Valcamonica
were further sub-classified in three areas including upper- (n = 23),
mid- (n = 85), lower- (n = 46) Valcamonica.
Gender was equally distributed between females (49.2%) and
males (50.8%), and median age was 155 months, with 18.3% of
11 years, 33.8% of 12 years, 40.5% of 13 years, 7.4% of 14 years old
subjects. SES was low in 24.8%, medium in 41.2% and high in 34% of
the families, and maternal education low in 38%, medium in 52.3%
and high in 9.7% of the cases. Participants with no siblings were
15.3%, one sibling 61.7%, two siblings 19.5%, three or more 3.6%.
Parity order was first in 52%, second in 38.3% and third or more in
9.7% of the cases. Alcohol consumption was declared by 9 subjects
(3%), and cigarette smoking by 3 subjects (1%). Median BMI was
20.0, similar to the results from other Italian surveys (Toselli et al.,
2010) and the reference Italian standards (Cacciari et al., 2006).
Clinical values for CBC, liver and kidney function, and physiological
iron status for the 311 included subjects were all within the
normal clinical range. No significant differences occurred among
the study sites for all socio-demographic covariates except for
the SES, that resulted higher among the Garda Lake subjects
(chi-squared = 7.4783, df = 2, p-value = 0.02377).
3.2. Exposure assessment
Data on Mn exposure assessment are summarized in Table 1a
with a comparison between the Valcamonica and Garda Lake
areas, and in Table 1b with sub-grouping of Valcamonica
according to the former location of the three ferroalloy plants.
The average values for the entire Valcamonica were: MnH
0.16 mg/g (median 0.11), MnB 10.99 mg/L (median 10.8), MnU
0.22 mg/L (median 0.10), Mn Air 49.47 ng/m3 (median 31.39), Mn
Soil 958.16 ppm (median 897.49). No significant differences were
noted for the biomarkers MnH, MnB, and MnU between
Valcamonica and Garda Lake, although a tendency toward
increased levels from the lower to mid-upper valley was noticed
for all biomarkers. The mean levels of Pb in blood were extremely
low in subjects in both study areas: Valcamonica mean 1.72 mg/dL
(median 1.60), Garda Lake 1.60 mg/dL (median 1.40). The
concentration of Mn in airborne particles was higher in
Valcamonica, especially in the mid valley (median 51.73 ng/
m3), compared to the Garda Lake reference area (median 24.72 ng/
m3). Concentrations of the other metals indicated a similar trend
for Pb, Cr, Fe, Ni, whereas Cu and Zn were higher in the Garda Lake,
possibly due to the agricultural use of chemical products (data not
shown). Airborne PM10 particles were also slightly higher in mid
Valcamonica (mean 71.64, median 62.22 mg/m3) compared to the
Garda Lake (mean 63.76, median 59.93 mg/m3). The subjects’
diaries kept over the 24 h air sampling period showed an average
of 2 h outdoor and 22 h indoor, with slight seasonal variation (1 h
outdoor in winter time and 3–5 h in spring time), and no variation
across the different study areas. Data on rain precipitation showed
that 46% of air particles were collected over 24 h periods that
contained some rain, while 54% were collected with no rain during
the sampling time, with slight differences between the Valcamonica (40% rain and 60% no rain) and Garda Lake (58% rain and
42% no rain) areas.
Soil values showed a significant increase from the lowest
concentration in Garda Lake to the lower-, mid-, upper-Valcamonica sub-areas for Mn and for Pb, Fe, Zn, As, Ni (data not shown).
The concentrations of heavy metals in tap water, reflecting the
public water supply from either study area, were not elevated. In
fact, water Mn levels were below the LDL of 1 mg/L in all water
samples. Only two subjects from Valcamonica (1.30% of participants) and two subjects from the Garda Lake (1.27% of
participants) reported drinking water from private wells. The
estimated daily oral intake of Mn based on dietary questionnaire
was 2.91 1.5 mg/day (median 2.66, range 0.72–9.46) for all
participants, with no area differences.
Table 1a
Manganese exposure assessment in biomarkers and environmental media (VC, ValCamonica; GL, GardaLake).
Variable
Levels
n
Mn hair (ppm)
VC
GL
All
125
133
258
0.02
0.02
0.02
0.07
0.06
0.06
0.16
0.18
0.17
0.11
0.12
0.11
0.19
0.20
0.19
1.27
3.45
3.45
0.12
0.14
0.13
29
24
53
VC
GL
All
151
148
299
4.00
6.00
4.00
8.70
8.90
8.80
10.99
11.24
11.11
10.80
10.95
10.90
13.15
12.80
12.90
21.60
24.10
24.10
4.45
3.90
4.10
3
9
12
VC
GL
All
151
150
301
0.10
0.10
0.10
0.10
0.10
0.10
0.22
0.16
0.19
0.10
0.10
0.10
0.10
0.10
0.10
7.60
1.50
7.60
0.00
0.00
0.00
3
7
10
VC
GL
All
125
64
189
1.24
5.30
1.24
15.12
16.92
15.38
49.47
27.37
41.99
31.39
24.72
29.37
60.21
35.99
47.20
516.70
85.93
516.70
45.09
19.06
31.82
29
93
122
VC
GL
All
31
27
58
464.88
159.76
159.76
658.93
352.95
441.66
958.16
426.58
710.70
897.49
408.58
579.13
1281.06
484.14
924.80
1729.10
734.02
1729.10
622.13
131.19
483.14
123
130
253
p = 0.74287
Mn blood (mg/L)
p = 0.54844
Mn urine (mg/L)
p = 0.74242
Mn air (ng/m3)
p = 0.03461
Mn soil (ppm)
p < 0.0001
Min
1st q.le
Mean
Median
3rd q.le
Max
IQR
#NA
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Table 1b
Manganese exposure assessment in biomarkers and environmental media (VC, ValCamonica; GL, GardaLake). The Valcamonica area is subdivided in the locations of the three
exposure sources from ferroalloy plants.
Variable
Levels
n
Mn hair (ppm)
Upper VC
Mid VC
Lower VC
GL
All
21
54
23
104
202
0.03
0.02
0.03
0.02
0.02
0.08
0.07
0.05
0.06
0.06
0.23
0.14
0.11
0.13
0.14
0.13
0.11
0.07
0.10
0.10
0.26
0.19
0.14
0.17
0.18
1.13
0.65
0.49
0.72
1.13
0.18
0.11
0.09
0.11
0.12
2
31
23
53
109
Upper VC
Mid VC
Lower VC
GL
All
22
83
46
148
299
7.10
4.00
5.30
6.00
4.00
9.03
8.70
8.55
8.90
8.80
12.54
10.80
10.59
11.24
11.11
12.60
10.90
10.20
10.95
10.90
14.78
12.85
12.07
12.80
12.90
21.60
17.20
18.20
24.10
24.10
5.75
4.15
3.52
3.90
4.10
1
2
0
9
12
Upper VC
Mid VC
Lower VC
GL
All
22
83
46
150
301
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.13
0.28
0.15
0.16
0.19
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.40
7.60
0.50
1.50
7.60
0.00
0.00
0.00
0.00
0.00
1
2
0
7
10
Upper VC
Mid VC
Lower VC
GL
All
22
62
41
64
189
8.22
7.79
1.24
5.30
1.24
16.86
29.78
5.25
16.92
15.38
31.34
71.53
25.86
27.37
41.99
23.97
51.73
15.11
24.72
29.37
34.91
89.57
35.51
35.99
47.20
115.32
516.70
243.10
85.93
516.70
18.05
59.80
30.26
19.06
31.82
1
23
5
93
122
Upper VC
Mid VC
Lower VC
GL
All
7
6
18
27
58
1261.56
650.73
464.88
159.76
159.76
1340.09
860.40
570.69
352.95
441.66
1474.41
1060.77
723.19
426.58
710.70
1433.72
1081.26
713.20
408.58
579.13
1608.16
1283.33
872.77
484.14
924.80
1729.10
1413.88
1008.85
734.02
1729.10
268.07
422.93
302.08
131.19
483.14
16
79
28
130
253
Max
IQR
#NA
p = 0.1434a
Mn blood (mg/L)
p = 0.1755
Mn urine (mg/L)
p = 0.7577
Mn air (ng/m3)
p < 0.0001
Mn soil (ppm)
p < 0.0001
a
Min
1st q.le
Mean
Median
3r q.le
Max
IQR
#NA
Kruskal–Wallis test.
Table 2
Significant differences for neurobehavioral test at the site comparison (VC, ValCamonica; GL, GardaLake; CE, closed eyes).
Variable
Levels
n
Sniffin test
GL
VC
All
156
152
308
GL
VC
All
p = 0.0045707
Aiming Pursuit
p = 0.012798
Luria Nebraska
p = 0.0018979
Sway intensity CE
p = 0.055633
Min
1st q.le
Mean
Median
3rd q.le
5.00
4.00
4.00
9.00
9.00
9.00
10.08
9.61
9.85
10.00
10.00
10.00
11.00
11.00
11.00
12.00
12.00
12.00
2.00
2.00
2.00
1
2
3
156
152
308
2.00
0.00
0.00
23.00
21.75
23.00
58.63
44.39
51.60
48.50
37.00
41.00
85.50
61.25
71.00
251.00
189.00
251.00
62.50
39.50
48.00
1
2
3
GL
VC
All
156
151
307
31.00
37.00
31.00
58.00
53.00
55.00
67.54
62.76
65.19
66.00
61.00
64.00
76.25
70.00
73.00
107.00
98.00
107.00
18.25
17.00
18.00
1
3
4
GL
VC
All
156
152
308
0.92
1.30
0.92
4.01
4.33
4.13
5.10
5.50
5.30
4.79
5.21
5.03
6.23
6.45
6.33
15.19
12.06
15.19
2.22
2.12
2.19
1
2
3
3.3. Neuro-psychological testing
Differences between Valcamonica and Garda Lake subjects
were noted for health outcomes including Sniffin’ sticks task
(p = 0.005), Aiming Pursuit test (p = 0.01), the Luria-Nebraska
partial motor scale (p = 0.002), and body sway with closed eyes
(p = 0.05) (Table 2). The multivariate analysis with GAM and
(Generalized Linear Model-GLM) logistic models showed a
significant association of soil Mn levels with the Luria-Nebraska
motor coordination test (Table 3, Fig. 3), with the Aiming Pursuit
hand steadiness test (Table 4, Fig. 4) and with Sniffin’ sticks odor
identification task (Table 5, Fig. 5). The smooth curves are
represented using penalized regression splines with smoothing
parameters selected by Generalized Cross Validation (Wood,
2006). A significant association was also observed between MnH
and MnB and tremor intensity in the dominant hand, with a
border-line relation also between soil Mn and tremor intensity
Table 3
Adjusted effect of soil Mn on the Luria-Nebraska motor coordination test score,
ordinary least square model.
Estimate
Intercept
Gender (M vs F)
Age
SESa
SESb
Maternal educationa
Maternal educationb
Smoking habit
Alcohol consumption
Mn Soil
a
b
Medium vs low.
High vs low.
51.828
1.690
1.594
2.970
4.002
0.716
3.852
12.438
0.509
0.009
SE
11.495
1.534
0.906
2.091
2.465
1.847
3.269
7.861
4.613
0.002
T value
Pr(>jtj)
4.509
1.101
1.758
1.420
1.623
0.387
1.179
1.582
0.110
3.521
0.0000
0.2717
0.0798
0.1566
0.1056
0.6987
0.2396
0.1147
0.9122
0.0005
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R.G. Lucchini et al. / NeuroToxicology 33 (2012) 687–696
Table 4
Adjusted effect of soil Mn on the Aiming Pursuit hand dexterity test score, semiparametric (GAM) model.
Intercept
Gender (M vs F)
SESa
SESb
Maternal educationa
Maternal educationb
Smoking habit
Alcohol consumption
Non parametric
Age
Mn soil
a
b
Estimate
SE
z-Value
Pr(>jtj)
129.7736
4.8431
1.1482
5.4496
7.2377
4.1177
22.4593
4.5436
4.9641
3.0155
4.1185
4.9228
3.6392
6.4537
15.4284
9.1090
26.142
1.606
0.279
1.107
1.989
0.638
1.456
0.499
0.0000
0.1094
0.7806
0.2692
0.0477
0.5240
0.1466
0.6183
Approximate significance of smooth terms
Edf
Ref.df
F
p-Value
2.821
4.324
3.441
5.385
4.604
2.922
0.0023
0.0115
Medium vs low.
High vs low.
(Table 6). No association was observed between the health effects
outcomes and the other parameters of internal (MnU) and external
(Mn Air, Mn Water, Mn daily oral intake) exposure to Mn in the
regression models (data not shown). We checked for the presence
of residual confounding with a sensitivity analysis on the inclusion
of additional covariates in the models, including parity order,
family size, SES, maternal education, BMI, alcohol intake, smoking
habits, and concentration of Pb and other metals in air, soil
and water. These covariates were generally not statistically
significant when entered into the model and in any cases did
not change sensibly the regression coefficients associated with Mn
exposure. Age was positively associated with the motor and odor
tests, but not with tremor, indicating a better performance among
the most grown up subjects. A gender difference was observed for
odor identification (Table 5), and tremor (Table 6) with lower
performance and increased tremor intensity among boys. SES did
not generally influence motor and odor testing, whereas maternal
education was positively associated to odor identification
Fig. 4. Soil Mn and hand steadiness as measured by the Aiming Pursuit test.
(Table 5). Although declared by a small number of subjects,
alcohol consumption was negatively associated to odor identification (Table 5) and cigarette smoking increased tremor intensity
(Table 6).
Table 5
Adjusted effect of soil Mn on the olfactory test, semi-parametric (GAM) logistic
model.
Estimate
2.6179
0.2865
0.1117
0.3401
0.2203
0.6436
0.0624
0.5104
0.0004
Intercept
Gender (M vs F)
SESa
SESb
Maternal educationa
Maternal educationb
Smoking habit
Alcohol consumption
Mn soil
SE
z-Value
Pr(>jtj)
0.2363
0.0897
0.1208
0.1402
0.1050
0.1995
0.4490
0.2442
0.0001
11.079
3.196
0.925
2.427
2.098
3.226
0.139
2.090
2.937
0.0000
0.0014
0.3551
0.0152
0.0359
0.0013
0.8894
0.0366
0.0033
Non parametric
Approximate significance of smooth terms
Edf
Ref.df
F
p-Value
Age
4.076
4.623
22.354
0.0003
a
b
Medium vs low.
High vs low.
Table 6
Adjusted effect of various Mn sources on (log-transformed) tremor intensity,
semiparametric (GAM) model.
Estimate
Intercept
Gender (M vs F)
Smoking habit
Alcohol consumption
Mn air
Mn hair
Non-parametric
Fig. 3. Soil Mn and motor coordination as measured with the Luria-Nebraska test.
MN soil
Mn blood
2.2765
0.2564
0.4172
0.0153
0.0004
0.2089
SE
z-Value
0.0346
0.0413
0.1886
0.1130
0.0005
0.0813
65.817
6.213
2.213
0.135
0.928
2.569
Pr(>jtj)
0.0000
<0.0001
0.0279
0.8924
0.3541
0.0108
Approximate significance of smooth terms
Edf
Ref.df
F
p-Value
2.584
7.625
3.264
8.529
2.140
2.749
0.0903
0.0053
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R.G. Lucchini et al. / NeuroToxicology 33 (2012) 687–696
Fig. 5. Soil Mn and odor identification as measured with the Sniffing test.
4. Discussion
The present study shows an association between Mn exposure
reflected by Mn levels in surface soil, hair and blood and
impairment of motor coordination, hand dexterity, tremor
intensity and odor identification in adolescents living in Valcamonica, Italy. Although Mn is a recognized extrapyramidal
neurotoxicants in adults since the past century, the most recent
studies on exposed children have focused only on cognitive and
behavioral implications. Our work is the first showing clear Mnrelated motor dysfunction in children, that are very similar to those
already observed by our group in chronically exposed ferroalloy
workers (Lucchini et al., 1995, 1999). Furthermore, this observation is of particular interest given that in the same region we
observed a significantly increased prevalence of Parkinsonism in
adults, compared to national and international rates, as possibly
linked to increased environmental Mn levels in the Valcamonica
dust (Lucchini et al., 2007). It is also noteworthy that olfactory
impairment is considered an early sign of Parkinson’s disease with
a prevalence of 75% in PD patients. Our observed association of
early effects on motor and odor functions with the levels of Mn in
soil and not in airborne particles, or with biomarkers of internal Mn
exposure (MnH, MnB, MnU) may suggest that these effects are
related to past or cumulative environmental exposures rather than
current exposure. In fact, the adolescents from Valcamonica were
likely exposed to higher levels of Mn in their early life; they were
on average 5 years old, when the last ferroalloy plant ceased
production in 2001. Metals in soil serve as good indicators of
general environmental insult because they are stable and longlived in the environment, and accumulate in soils over time (Aelion
et al., 2009). As such, Mn levels in surface soil measured here would
be expected to reflect background soil Mn in addition to
cumulative inputs from atmospheric deposition of ferroalloy plant
emissions, and thus appear to be a reasonable proxy of past
cumulative Mn exposure to the children in this study.
Although still preliminary, the analysis of hair data (that will be
fully reported elsewhere) has showed an association with tremor
intensity. Hair Mn levels may serve as a better indicator of
integrated exposure and acquired body burden over the prolonged
period of hair growth, differently from MnB and MnU, which are
under rapid homeostatic control. The rigorous cleaning procedure
developed for hair samples in this study were designed to
minimize risk of external Mn contamination without compromising endogenous (metabolic) Mn, and thereby may have improved
the sensitivity of this exposure biomarker to predict the internal
dose in storage organs and tissues. Since tremor intensity is related
to MnB, this health outcome may be related to current rather than
to cumulative exposure.
The detailed exposure assessment, exploring all relevant
sources and potential exposure biomarkers, was a major strength
of this study. Subject-based measurement of airborne particles
over 24 h still shows higher levels of metals in the mid-upper
valley compared to the reference area about 7 years after the
cessation of active ferroalloy plant emissions. This may be best
explained by the weathering and re-suspension of surface particles
due heavy traffic, unpaved roads, road/work construction in the
Valcamonica. In addition, residual atmospheric emission from
other industries located in the mid valley cannot be excluded. Very
few air exposure data obtained with personal sampling are
available for comparison. Pellizzari et al. (2001) reported lower Mn
concentration in PM10 and PM2.5 (median 8 ng/m3) from Toronto
and Indianapolis. Background average levels of 10 ng/m3 have also
been recently surveyed in urban areas in Spain, rising to 25 ng/m3
in industrial sites (Moreno et al., 2011). The current reference
concentration for airborne Mn of USEPA and Health Canada in
Canada is 50 ng/m3 (Health Canada, 2010). The soil Mn levels were
relatively consistent in showing an increasing gradient from the
lower to the upper Valcamonica, which may be explained by the
day time prevailing wind direction (South to North) and also by an
overlap of anthropogenic emission on naturally higher soil Mn
levels in the upper Valcamonica. This was shown by previous
fingerprint analysis of metals in the deposited dust sampled in the
entire province of Brescia (Zacco et al., 2009). Further, differences
regarding the ferroalloy plants previously operating in the three
sub-areas of Valcamonica can partially explain the differences of
metal concentrations in airborne particles and surface soil in these
sub-areas. The lower Valcamonica shows air levels of metals and
PM10 that are similar to the Garda Lake, probably because the
plant in this area was closed in 1995, which is more than 10 years
before this study. The mid-valley shows the highest air levels
probably because the plant in this area was closed most recently in
2001 and because particle re-suspension and residual industrial
emissions are still present in this area. The ferroalloy plant in the
upper valley was mainly a holding/deposit site and for Mn-rich
ores shows the highest soil Mn levels.
In this study, the very low levels of Mn in tap water indicate
drinking water does not represent a notable source of exposure.
The observed levels below 1 mg/L are substantially lower than the
current guideline of 400 mg/L set by the World Health Organization
and the U.S. health reference level of 300 mg/L (Ljung and Vahter,
2007). They are also lower than drinking water Mn levels
associated with cognitive deficits in children from Québec, where
water Mn levels ranged from 0.1 to 2700 mg/L (median 30.8)
(Bouchard et al., 2011), and Bangladesh, where water Mn levels
averaged 795 755 mg/L (Wasserman et al., 2006). Water from the
public supply system in the province of Brescia is treated to decrease
the Mn level for esthetic reasons. This treatment is generally lacking
in private wells, where Mn concentrations may reach high levels
(Ljung and Vahter, 2007), but the use of water from private wells was
very limited in the present study. Mn oral intake resulted in 81% (118
girls and 130 boys) above the Adequate Intake (AI) by the Institute of
Medicine, for children 9–13 years of age (1.6 mg/d for girls; 1.9 mg/d
for boys) and in 5% above the Upper Intake Level (UL) of 6 mg/d,
although within the range of data reported in the literature (Ljung and
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R.G. Lucchini et al. / NeuroToxicology 33 (2012) 687–696
Vahter, 2007). Levels of Mn in blood, urine, or hair were not
measurably different in subjects from the impacted Valcamonica
versus Garda Lake reference areas, although MnB, MnU and MnH
were slightly higher in the subjects from the mid-upper Valcamonica
compared to the other two areas (lower Valcamonica or Garda Lake).
Blood levels of Mn were similar to those recently measured in 359
school children aged 8–16 years from Durban, South Africa
(10.1 3.4 mg/L, median 9.6), exposed to similar Mn levels in
PM10 airborne particles (48.7 44 ng/m3, median 34.3) (Batterman
et al., 2011). This is the first study that shows MnH associated with
extra-pyramidal impairment. Hair Mn levels have been associated
with cognitive deficits in other studies (Wright et al., 2006; Bouchard
et al., 2011; Riojas-Rodrı́guez et al., 2010; Menezes-Filho et al., 2011),
though the extent that hair Mn levels reported in those studies
reflects external contamination versus internal body burden is not
clear, since the hair cleaning methodologies varied widely in those
studies, and all of them were notably less rigorous than the methods
used in the present study.
A limitation of this study may be the possible residual
confounding by unobserved variables. The study is based on a
comparison between two adolescents populations that we
assumed to be similar but for the exposure and confounding
variables that we have recorded. Another limitation may be the
association of the exposure location with the subject’s home.
Although the majority of the time was spent by each adolescent in
the house (17 h on average), another 5 h were spent at school and
2 h outdoors, including road transportation. Different exposure
levels, especially for airborne particles, may have characterized the
different sites. Nevertheless, even considering these limitations,
the study indicates that living in an environment characterized by
long-term exposure to metals – particularly Mn, can lead to
impairment in the development of motor and olfactory functions
that may be potentially considered as an early warning for the
onset of late neurodegenerative effects in the older age. Preventive
strategies toward sustainable soil should be promoted for urban
areas close to metal emission from industries and further study
should clarify the soil chemistry to allow better understanding of
metal solubility, transport and bio-accessibility to plants and living
organisms. Further research is scheduled in the Province of Brescia
and will target the area of Bagnolo Mella, in the proximity of a
currently active ferroalloy plant. This will provide further
comparison with human populations exposed to higher levels of
metals typically released in the environment by the ferroalloy
production.
In summary, this is the first study showing association of
manganese in surface soil and airborne particles with motor
coordination, hand dexterity and odor identification and of
manganese in blood and hair with tremor, in adolescents residing
in areas with previous long term emission of metals – including
manganese – from ferroalloy emission. The measurement of
manganese in soil may represent an indicator of historical
cumulative exposure.
Conflict of interest statement
Zimmerman had paid expert testimony/consulting for plaintiff
manganese exposure welder/welding rod lawsuits, and all the
remainder of authors had declared no conflict of interest.
Acknowledgements
This study was supported by funding from the European Union
through its Sixth Framework Program for RTD (contract no FOODCT-2006-016253). It reflects only the authors’ views, and the
European Commission is not liable for any use that may be made of
the information contained therein. The project was supported also
695
by Award Number R01ES019222 from the National Institute of
Environmental Health Sciences (NIEHS). The content is solely the
responsibility of the authors and does not necessarily represent the
official views of the NIEHS or the National Institutes of Health.
References
Aelion CM, Davis HT, McDermott S, Lawson AB. Soil metal concentrations and toxicity:
associations with distances to industrial facilities and implications for human
health. Sci Total Environ 2009;407(7):2216–23.
Apostoli P, Lucchini R, Alessio L. Are current biomarkers suitable for the assessment of
manganese exposure in individual workers? Am J Ind Med 2000;37(3):283–90.
Aschner M, Erikson KM, Dorman DC. Manganese dosimetry: species differences and
implications for neurotoxicity. Crit Rev Toxicol 2005;35(1):1–32.
Aschner M, Dorman DC. Manganese: pharmacokinetics and molecular mechanisms of
brain uptake. Toxicol Rev 2006;25(3):147–54.
Batterman S, Su FC, Jia C, Naidoo RN, Robins T, Naik I. Manganese and lead in children’s
blood and airborne particulate matter in Durban, South Africa. Sci Total Environ
2011;409(6):1058–68.
Bivand RS, Pebesma EJ, Goméz-Rubio V. Applied spatial data analysis with R. New York:
Springer; 2008.
Borgese L, Zacco A, Pal S, Bontempi S, Lucchini R, Zimmerman N, et al. A new nondestructive method for chemical analysis of particulate matter filters: the case of
manganese air pollution in Vallecamonica (Italy). Talanta 2011;84:192–8.
Borgese L, Salmistraro M, Gianoncelli A, Zacco A, Zimmerman N, Lucchini R, et al.
Airbone particulate matter (PM) filter analysis and modeling by total reflection Xray fluorescence (TXRF) and X-ray standing wave (XSW). Talanta 2012;89:99–104.
Bouchard MF, Sauvé S, Barbeau B, Legrand M, Brodeur MÈ, Bouffard T, et al. Intellectual
impairment in school-age children exposed to manganese from drinking water.
Environ Health Perspect 2011;119(1):138–43.
Cacciari E, Milani S, Balsamo A, Spada E, Bona G, Cavallo L, et al. Italian cross-sectional
growth charts for height, weight and BMI (2 to 20 yr). J Endocrinol Invest
2006;29(7):581–93.
Calderón-Garcidueñas L, Franco-Lira M, Henrı́quez-Roldán C, Osnaya N, GonzálezMaciel A, Reynoso-Robles R, et al. Urban air pollution: influences on olfactory
function and pathology in exposed children and young adults. Exp Toxicol Pathol
2010;62(1):91–102.
Depero LE, Bontempi E, Borgese L, Zacco A, Lucchini RG. Method for the analysis of
samples and sample. International patent no. WO/2009/116107; publication date
24.09.2009, http://www.wipo.int/pctdb/en/wo.jsp?WO=2009116107.
Després C, Lamoureux D, Beuter A. Standardization of a neuromotor test battery: the
CATSYS system. Neurotoxicology 2000;21:1–11.
Elder A, Gelein R, Silva V, Feikert T, Opanashuk L, Carter J, et al. Translocation of inhaled
ultrafine manganese oxide particles to the central nervous system. Environ Health
Perspect 2006;114:1172–8.
Fleischman EA. Dimensional analysis of psychomotor abilities. J Exp Psychol
1954;48:437–54.
Golden CJ, Hammeke T, Purish A. Manual for the Luria Nebraska neuropsychological
battery. Western Psychological Services: Los Angeles; 1980.
Harrell FE. Regression modeling strategies with applications to linear models, logistic
regression, and survival analysis. New York: Springer; 2001.
Health Canada. Human health risk assessment for inhaled manganese. 2010 Available
on Internet at: http://www.healthcanada.gc.ca/.
Hummel T, Bensafi M, Nikolaus J, Knecht M, Laing DG, Schaal B. Olfactory function in
children assessed with psychophysical and electrophysiological techniques. Behav
Brain Res 2007;180:133–8.
Iregren A, Gamberale F, Kjellberg A. SPES: a psychological test system to diagnose
environmental hazards. Neurotoxicol Teratol 1996;18:485–91.
Leclercq C, Arcella D, Piccinelli R, Sette S, Le Donne C, Turrini A, et al. The Italian
National Food Consumption Survey INRAN-SCAI 2005–06: main results in terms of
food consumption. Public Health Nutr 2009;12(12):2504–32.
Ljung K, Vahter M. Time to re-evaluate the guideline value for manganese in drinking
water? Environ Health Perspect 2007;115(11):1533–8.
Lucchini R, Selis L, Folli D, Apostoli P, Mutti A, Vanoni O, et al. Neurobehavioral effects
of manganese in workers from a ferroalloy plant after temporary cessation of
exposure. Scand J Work Environ Health 1995;21:143–9.
Lucchini R, Apostoli P, Perrone C, Placidi D, Albini E, Migliorati P, et al. Long-term
exposure to low levels of manganese oxides and neuro-functional changes in
ferroalloy workers. Neurotoxicology 1999;20(2–3):287–97.
Lucchini RG, Albini E, Benedetti L, Borghesi S, Coccaglio R, Malara EC, et al. High
prevalence of Parkinsonian disorders associated to manganese exposure in the
vicinities of ferroalloy industries. Am J Ind Med 2007;50(11):788–800.
Lucchini RG, Dorman DC, Elder A, Veronesi B. Neurological impacts from inhalation of
pollutants and the nose-brain connection. Neurotoxicology 2012;33(4):838–41.
Menezes-Filho JA, Novaes CdeO, Moreira JC, Sarcinelli PN, Mergler D. Elevated manganese and cognitive performance in school-aged children and their mothers. Environ Res 2011;111(1):156–63.
Moreno T, Pandolfi M, Querol X, Lavı́n J, Alastuey A, Viana M, et al. Manganese in the
urban atmosphere: identifying anomalous concentrations and sources. Environ Sci
Pollut Res 2011;18:173–83.
Pellizzari ED, Clayton CA, Rodes CE, Mason RE, Piper LL, Fort B, et al. Particulate matter
and manganese exposures in Indianapolis, Indiana. J Expo Anal Environ Epidemiol
2001;11:423–40.
Author's personal copy
696
R.G. Lucchini et al. / NeuroToxicology 33 (2012) 687–696
R Development Core Team. R: a language and environment for statistical computing.,
Vienna, Austria: R Foundation for Statistical Computing; 2011 In: http://www.
R-project.org.
Riojas-Rodrı́guez H, Solı́s-Vivanco R, Schilmann A, Montes S, Rodrı́guez S, Rı́os C,
et al. Intellectual function in Mexican children living in a mining area and
environmentally exposed to manganese. Environ Health Perspect 2010;118(10):
1465–70.
Toselli S, Argnani L, Canducci E, Ricci E, Gualdi-Russo E. Food habits and nutritional
status of adolescents in Emilia-Romagna, Italy. Nutr Hosp 2010;25(4):613–21.
USDA. U.S. Department of Agriculture, Agricultural Research Service. USDA National
Nutrient Database for Standard Reference, Release 23. 2010 Nutrient Data Laboratory Home Page, http://www.ars.usda.gov/ba/bhnrc/ndl.
Venables WN, Ripley BD. Modern Applied Statistics with S. 4th ed. Springer; 2002.
Wasserman GA, Liu X, Parvez F, Ahsan H, Levy D, Factor-Litvak P, et al. Water
manganese exposure and children’s intellectual function in Araihazar, Bangladesh.
Environ Health Perspect 2006;114(1):124–9.
Wood SN. Generalized additive models: an introduction with R. CRC/Chapman & Hall;
2006.
Wright RO, Amarasiriwardena C, Woolf AD, Jim R, Bellinger DC. Neuropsychological
correlates of hair arsenic, manganese, and cadmium levels in school-age children
residing near a hazardous waste site. Neurotoxicology 2006;27(2):210–6.
Zacco A, Resola S, Lucchini R, Albini E, Zimmerman N, Guazzetti S, et al. Analysis of
settled dust with X-ray fluorescence for exposure assessment of metals in the
province of Brescia, Italy. J Environ Monit 2009;11(9):1579–85.
Zoni S, Albini E, Lucchini R. Neuropsychological testing for the assessment of manganese neurotoxicity: a review and a proposal. Am J Ind Med 2007;50(11):812–30.