Gender as a key factor in trace metal and metalloid content of human scalp hair. A multi-site study

Science of the Total Environment 573 (2016) 996–1002

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Gender as a key factor in trace metal and metalloid content of human scalp hair. A multi-site study Tamburo E. ⁎, Varrica D., Dongarrà G. Dip. Scienze della Terra e del Mare (DiSTeM), via Archirafi 22, 90123, Palermo, Italy

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Gender is a confounding factor in the interpretation of metal profiles in human hair. • Gender effect can significant impact on the application of the common coverage intervals. • The content of some trace elements in human hair is statistically different between female and male, regardless of the residence site. • Adolescent girls exhibit significantly higher hair concentrations of Sr, Zn and Ni than boys.

a r t i c l e

i n f o

Article history: Received 27 May 2016 Received in revised form 25 August 2016 Accepted 26 August 2016 Available online xxxx Editor: D. Barcelo Keywords: Metals and metalloids in human scalp hair Hair analysis Gender related differences Human biomonitoring Coverage intervals

a b s t r a c t This multi-site study discusses the content of metals and metalloids (MM) in scalp hair of children, living in different environmental contexts, with the purpose of verifying if hair level of some MM is distinctively gender-specific. A total of 943 hair samples (537 females and 406 males) from adolescents were analyzed for their content of Al, As, Ba, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Rb, Sb, Se, Sr, U, V and Zn. Elemental quantification was performed by ICP-MS. The obtained data identified different metal distributions in adolescent girls which exhibited significantly higher hair concentrations of some trace metals, especially Sr, Zn and Ni, than boys. On the base of the median value, hair of female donors contained 3.8 times more Sr (6.6 μg/g) than males (1.7 μg/g). Highest concentrations of Zn in females were observed in samples from the mining area of Sardinia (587 μg/g). Nickel showed significant differences resulting 2.5-fold higher in female hair. Regardless of the residence site, these elements resulted always significantly different (at p b 0.01) between female and male indicating that gender is a confounding factor that has to be more extensively considered for a correct interpretation of metal profiles in human hair. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Exposure of people to trace metals and metalloids (MM) is an issue that raises many public concerns and debates because of their large⁎ Corresponding author. E-mail address: [email protected] (T. E.).

http://dx.doi.org/10.1016/j.scitotenv.2016.08.178 0048-9697/© 2016 Elsevier B.V. All rights reserved.

scale use in almost all industrial, agricultural, and technological applications and their potential effects on human health (Combs, 2005; Biggeri et al., 2006; Manno et al., 2006; Tamim et al., 2016). Ingestion of food (vegetables, meat, fish) or water, dust inhalation and also dermal

T. E. et al. / Science of the Total Environment 573 (2016) 996–1002

contact are the main ways of human exposure to MM (US EPA, 1989, 1996; Islam et al., 2014, 2015, 2016; López-Alonso et al., 2016). Metals and metalloids, even at trace concentration levels, play a variety of essential roles in the human body which employs them, at different extent, to maintain normal yet complex biochemical and physiological functions (Lindh, 2005; Combs, 2005). However, adverse effects on human health may derive from either dietary excess or abnormal exposure (WHO, 1996; Aggett et al., 2015; Nordberg and Nordberg, 2016). To assess human exposure to potentially toxic elements, human biomonitoring (HBM) is a scientific approach which develops through measurement of chemicals or their metabolites in body fluids and tissues, such as blood (Alimonti et al., 2005; Sanna et al., 2007, 2008, 2011; Gil et al., 2011; Liu et al., 2012; Richmond-Bryant et al., 2013; Coelho et al., 2014), plasma (Vural et al., 2010; Knerr et al., 2013), serum (Alimonti et al., 2005; Klimenko et al., 2016), breast milk (Aquilio et al., 1996; Yamawaki et al., 2005), urine (Berglund et al., 2011; Gil et al., 2011; Sanna et al., 2011; Coelho et al., 2014), lung fluids (Censi et al., 2011a, 2011b), nail (Carneiro et al., 2011a; Coelho et al., 2014) and also hairs (Bencko, 1995; D'Ilio et al., 2000; Violante et al., 2000; Pereira et al., 2004; Amaral et al., 2008; Rodrigues et al., 2008; Sanna et al., 2007, 2008, 2011; Bormann de Souza et al., 2009; Carneiro et al., 2011a, 2011b; Coelho et al., 2014; Mikulewicz et al., 2015). Among these matrices, scalp hair, because of its structure, mainly composed of fibrous keratinocytes, and especially of cystine, the primary amino acid of this protein, constitutes an optimal matrix for HBM due to its ability to accumulate MM in response to dietary intakes and other exposures at a greater extent than other biological matrices and for a longer time frame (ATSDR, 2001; Rodushkin and Axelsson, 2000; Gellein et al., 2008; Rodrigues et al., 2008; Esteban and Castaño, 2009; Abbruzzo et al., 2016). Even though hair results do not provide quantitative dose-response relationships and their possible clinical significance they constitute an useful tool for screening procedures of exposure. Moreover, scalp hair sampling and analysis possess a number of important advantages over other matrices, including: non-invasive and painless collection, easy transport, storage and chemical inertness of samples (ATSDR, 2001; Esteban and Castaño, 2009) and small specimen size required for analysis. Despite these vantages, several researchers argue some drawbacks in the interpretation of readings based on hair mineral analysis. Most of these are related to: (1) the scarce theoretical knowledge of the biochemical mechanisms involved in the uptake of MM (ATSDR, 2001); (2) hair analysis results may not relate to MM levels in blood, urine and other target tissues (ATSDR, 2001; Esteban and Castaño, 2009); (3) no uniform opinions on the standard hair analysis protocol (for example the need to wash the samples before analysis (Kempson and Lombi, 2011); (4) inadequacy of reference intervals estimated without taking into account age, gender and ethnicity (Harkins and Susten, 2003; Barbosa et al., 2005; Dongarrà et al., 2011; Tamburo et al., 2015a). With regard to this last point, may be worth noting that trace elements in human hair may depend on several factors as gender, hair color, eating habits, age and lifestyle (Sturaro et al., 1994; Chojnacka et al., 2006, 2010a, 2010b; Zaichick and Zaichick, 2010; Skalnaya et al., 2015; Pan and Li, 2015; Skalny et al., 2015). Age-specific reference values for some chemical elements were reported by Vanaelst et al. (2012); Zaichick and Zaichick (2010) and Skalnaya et al. (2015). Site-specific reference values for human hair from urban population may be found in Senofonte et al. (2000); Park et al. (2007); Carneiro et al. (2011b); Dongarrà et al. (2011); Vanaelst et al. (2012); Peña-Fernández et al. (2014) and Skalnaya et al. (2015). Differences in the metal content of hair samples from people living close to mining or volcanic areas as well as in urban and industrialized areas have been also reported (Amaral et al., 2008; Dongarrà et al., 2011, 2012; Barbieri et al., 2011; Varrica et al., 2014a, 2014b; Tamburo et al., 2015a). To estimate causal relationships between environmental factors, human health and the level of trace elements in hair extensive use of

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coverage intervals (CI) is made. As recommended by International Union of Pure and Applied Chemistry (IUPAC) (Poulsen et al., 1997), they refer to concentration intervals, generally between the 0.025 and 0.975 fractiles, computed from a well-defined group of individuals reflecting normal and healthy people. A critical point in the efficient use of CI, when used for comparative decision-making processes, forensic and clinic considerations, is constituted by the presence of potential confounding factors as the living site of the study population and the specific characteristics of the participants. In particular, the different behavior of female and male with respect to MM content in human hair is rarely taken into account, although it appears to be a key factor in trace metal and metalloid content of human scalp hair (Chojnacka et al., 2006, 2010a, 2010b; Sanna et al., 2007, 2008, 2011; Vahter et al., 2007; Peña-Fernández et al., 2014; Varrica et al., 2014a, 2014b; Tamburo et al., 2015b). The aim of this paper is to further show, by some examples, that the coverage intervals for some trace elements in human hair may be gender-specific. To this purpose 943 hair samples from adolescents of both genders, living in industrial, urban, volcanic and polymetallic mining areas were taken into account. 2. Material and methods 2.1. Sample collection A total of 943 hair samples from adolescents, from 11 to 14 years old, were analyzed for their content of Al, As, Ba, Cd, Co, Cr, Cu, Li, Mn, Mo, Ni, Pb, Rb, Sb, Se, Sr, U, V and Zn. Donors were 537 females and 406 males, all of them responding to the following exclusion criteria: − − − − − −

non-Caucasian ethnicity; living in the selected area for b5 years; presence of diseases; habitual use of cigarettes; recent surgery or orthodontic treatment; colored hair or recent use of hairstyling products.

The use of mineral supplements was not considered during the sampling as being unlikely. Hair samples were categorized into four groups to which the following labels were assigned: Samples from industrial areas (IA): − Pace del Mela, a coastal town near Messina (north-eastern Sicily), is an area at high environmental risk, due to the presence of a large petrochemical plant. Outcropping rocks in the study area are mainly of sedimentary origin, with alternating sandstone, clay, limestone, ivory-white calcareous marl, calcarenite and sand; Ntotal = 111 (mean age: 12.6 ± 0.95), Nmale = 47 (mean age: 12.7 ± 0.90), Nfemale = 64 (mean age: 12.6 ± 1.0; percentage of girls who reached menarche: 70%); − Gela, Butera and Niscemi are located in southwestern Sicily and, from a geological point of view, they lie on sedimentary rocks represented by limestone, clay, marly-clay, white or yellow quaternary biocalcarenites and gypsum. The municipalities of Gela, Butera and Niscemi were declared “area at high risk of environmental crisis”, since 1986 (Law n. 349/1986) due to the presence of a large oil refinery, together with a number of important chemical and petrochemical industries that led to the definition of “site of national concern for soil remediation” (Law n. 426/1998); Ntotal = 174 (mean age: 12.3 ± 0.96), Nmale = 81 (mean age: 12.4 ± 0.89), Nfemale = 93(mean age: 12.3 ± 1.03; percentage of girls who reached menarche: 52%);

Samples from polymetallic mining area (PA): − Iglesias and Sant'Antioco, are located in southwestern Sardinia. The large outcrops of sulfide and oxide ores, as well as the products of

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the long lasting mining activity, characterize the whole district with unusual concentrations of metals and metalloids. The mine wastes are close to the town of Iglesias whereas pyroclastic volcanic rocks outcrop in Sant'Antioco Island; Ntotal = 144 (mean age: 12.3 ± 0.94), Nmale = 60 (mean age: 12.4 ± 0.91), Nfemale = 84 (mean age: 12.2 ± 0.95; percentage of girls who reached menarche: 38%); Samples from a large urban area (UA): − Palermo, the largest city of Sicily located in NW Sicily, lithologically consists of sedimentary rocks: limestone, clay, marly-clay and white or yellow Quaternary biocalcarenite. Potential local pollutants are limited to emissions from vehicular traffic, house heating and small manufacturing industries; (Ntotal = 137 (mean age: 12.4 ± 0.71), Nmale = 37 (mean age: 12.3 ± 0.76), Nfemale = 100 (mean age: 12.5 ± 0.66; percentage of girls who reached menarche: 46%);

parametric approach was used. Mann–Whitney test was employed to compare differences in the chemical composition of hair samples from female and male donors. Coverage intervals (at a confidence level of 0.95) were computed with lower and upper limits fixed at 2.5th and 97.5th percentiles of the interval, according to the non-parametric approach recommended by the International Union of Pure and Applied Chemistry (IUPAC) (Poulsen et al., 1997). The limits of the coverage intervals (Table 1) were computed according to the following procedure: 1. Log transformation of raw data, after exclusion of outliers; 2. Sorting of values in ascending order; 3. Non-parametric estimate of the limits of the coverage interval between the 0.025 and 0.975 fractiles; 4. Estimate of the precision of the reference limits; 5. Back-transformation of the limits to the original units (μg/g).

Samples from a volcanic area (VA): − Several small towns located around Mt. Etna (Sicily), where the volcano is an important source of trace elements in the local environment, contributing around 16% to the global budget during eruptive periods and around 2% during normal degassing (Gauthier and Le Cloarec, 1998). Volcanic contribution to MM in air is significantly higher than local emissions of anthropogenic origin (Aiuppa et al., 2006), (Ntotal = 377 (mean age: 12.1 ± 0.91), Nmale = 181 (mean age: 12.2 ± 0.88), Nfemale = 196 (mean age: 12.0 ± 0.94; percentage of girls who reached menarche: 33%). According to the EU and national legal and ethical requirements, children's legal representatives signed consent forms authorizing sample collection. Personal data were entered in an anonymous format. All subjects were interviewed to obtain detailed information on their personal background. The data considered have been taken from literature (Dongarrà et al., 2011, 2012; Varrica et al., 2014a, 2014b; Varrica et al., 2015). 2.2. Analytical methods Strands of hair, about 1–1.5 cm long, were cut as close as possible to the occipital region of scalp and stored in plastic bags. In the laboratory, the samples were reduced into smaller fragments, repeatedly washed with 2-propanone and water, dried at low temperature (40 °C) for 24 h and weighed. Then, HNO3 (Suprapur, Merck) was added to washed hair sample and digested for 24 h. Digestion was completed for a further period of 24 h after having added H2O2 (Suprapur, Merck). The obtained solution was then diluted with 18 MΩ cm demineralized water. Quantification of trace elements was performed by inductively coupled plasma mass spectrometry (ICP-MS, Perkin-Elmer, Elan 6100 DRC-e) after the addition of Re–Sc–Y as internal standards, using the technique of the additions to minimize the matrix effect. Analytical precision, estimated from triplicate analyses every ten sample, was in the range ± 3–9% for all analyzed elements, except As and Li, whose precision was ± 12%. The validity of the analytical procedure was checked by the standard reference material QMEQAS08H-02 and QMEQAS08H-09 of the Institut National de Santé Publique – Centre de Toxicologie, Québec (Canada). The metal recovery rates of certified elements in the reference material ranged between 90% for As and 111% for Al. 2.3. Statistical approach Data were analyzed statistically by the Statsoft program, version 6.0 (2001). Kolmogorov–Smirnov's test, with a level of significance set at p b 0.01, was used to verify the normality of data distribution. As the statistical test showed that some predictors were highly skewed, a non-

3. Results Table 1 lists the main descriptive statistical parameters of metals and metalloids (MM) in human scalp hair regarding the total dataset and also the dataset broken down by gender. Coverage intervals calculated for each element differentiated by gender are also given. Table 1 shows that, in spite of the wide overlapping of the distributions, differences exist for most chemical elements. It is worth noting that the coverage intervals of Cd, Co, Cu, Mn, Ni, Sr, V and Zn are much wider for females than males, as well as those of Li and U computed for males extend far beyond those for females. The non-parametric Mann-Whitney test showed that, these differences were significant at p-level b 0.01, with the exception of U significant at p-level = 0.736. The Mann-Whitney test was also carried out on the dataset broken down by residence sites (Table 2) and it shows that, regardless of the residence site, Ni, Sr and Zn were always statistically different between female and male. Hair of female donors contained, on the base of median value, 3.8 times more Sr (6.6 μg/g) than males (1.7 μg/g). In addition, 15% of the analyzed hair samples from female subjects exceeded the 97.5th percentile of the concentrations of Sr in male subjects and 32% of these latters resulted lower than the 2.5th percentile in female hair. Regardless of the residence site, female group showed always higher and statistically different median concentrations of Sr than male group (IAFemale: 18.7 μg/g – IAMale: 4.95 μg/g; PAFemale: 2.2 μg/g – PAMale: 0.8 μg/g; UAFemale: 7.7 μg/g – UAMale: 3.4 μg/g; VAFemale: 4.4 μg/g – VAMale: 0.97 μg/g). We found higher level of hair Zn in females than in males and also that 69 out of 537 hair samples, corresponding to 13% of the analyzed female subjects, exceeded the 97.5th percentile of the concentrations of Zn in male hair and 7% of these latters were lower than the 2.5th percentile in female hair. Zn median concentrations were also statistically different in subgroups of samples collected within areas affected by the presence of petrochemical industries, in samples from the polymetallic mining area, in samples from a large urban area and in samples from a volcanic area (IAFemale: 203 μg/g – IAMale: 188 μg/g; PAFemale: 237 μg/g – PAMale: 221 μg/g; UAFemale: 192 μg/g – UAMale: 132 μg/g; VAFemale: 205 μg/g – VAMale: 196 μg/g). Also nickel showed significant differences between females and males, hair of female donors contained, on the base of the median value, 2.5 times more Ni (0.32 μg/g) than males (0.13 μg/g). Some samples, 51 out of 537 corresponding to 9% of the analyzed female subjects exceeded the 97.5th percentile of the male group while 17% of these latters resulted below 2.5th female lower limit. Regardless of the residence site, female group showed always higher median concentrations of Ni than male group (IAFemale: 0.3 μg/g – IAMale: 0.1 μg/g; PAFemale: 0.2 μg/ g – PAMale: 0.1 μg/g; UAFemale: 0.6 μg/g – UAMale: 0.04 μg/g; VAFemale: 0.2 μg/g – VAMale: 0.1 μg/g).

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Table 1 Descriptive statistical parameters(median, 25th and 75th percentile), non-parametricMann–Whitney test (p-value b 0.01) and coverage intervals for the analyzed chemical elements (μg/g dry-weight basis) in children's scalp hair. Probability values evidence significant differences between female andmale dataset. Coverage intervals computed according to the non-parametric approach recommended by IUPAC (Poulsen et al., 1997). Total dataset (n=943)

Al As Ba Cd Co Cr Cu Li Mn Mo Ni Pb Rb Sb Se Sr U V Zn

th

Median

25

5.0 0.03 1.07 0.01 0.04 0.11 13 0.02 0.31 0.04 0.22 0.63 0.01 0.02 0.50 3.9 0.03 0.1 200

3.6 0.009 0.51 0.01 0.02 0.06 10 0.01 0.18 0.02 0.12 0.30 0.00 0.01 0.36 1.7 0.01 0.1 172

Male group (n=406) 75

th

6.6 0.05 1.72 0.03 0.11 0.20 20 0.04 0.54 0.07 0.42 1.23 0.02 0.04 0.64 8.8 0.05 0.3 231

th

Median

25

4.8 0.03 0.79 0.01 0.03 0.12 11 0.02 0.27 0.04 0.13 0.57 0.01 0.03 0.54 1.7 0.03 0.1 194

3.4 0.01 0.37 0.00 0.01 0.07 9 0.01 0.17 0.02 0.06 0.27 0.01 0.01 0.39 0.7 0.01 0.1 164

75

th

6.2 0.05 1.43 0.02 0.07 0.21 15 0.04 0.44 0.06 0.23 1.14 0.02 0.04 0.68 4.2 0.05 0.2 217

Female group (n=537) th

Coverage interval

Coverage uncertainty (δ)

Median

25

0.01-10.6 0.0003-0.17 0.01-3.4 0.0003-0.18 0.003-0.45 0.005-0.46 7.1-45 0.002-0.40 0.01-1.6 0.0003-0.29 0.0003-0.81 0.03-4.0 0.001-0.18 0.005-0.10 0.13-1.4 0.22-18 0.001-0.19 0.01-0.96 110-295

0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021 0.021

5.0 0.03 1.28 0.02 0.05 0.10 15 0.02 0.34 0.05 0.32 0.71 0.01 0.02 0.49 6.6 0.03 0.2 208

3.7 0.01 0.73 0.01 0.02 0.06 12 0.01 0.20 0.03 0.18 0.34 0.00 0.01 0.34 3.2 0.01 0.1 179

4. Discussion The current literature reports examples of relationships between gender and distribution of trace elements in human scalp hair (Sakai et al., 2000; Khalique et al., 2006; Chojnacka et al., 2010a, 2010b; Zaichick and Zaichick, 2011; Molina-Villalba et al., 2015; Skalny et al., 2015). However, many studies may be found, especially in medical field, that use human hair analysis as clinical decision-making tool to predict some diseases without to ponder upon the role of gender (Ren et al., 1997; Man and Zheng, 2002; Pasha et al., 2007; Tan et al., 2009). In addition, coverage intervals are usually derived from distributions of measured concentrations of trace elements in donors irrespective of age, gender and residence site, even though the necessity for the use of site- and gender-specific reference values was suggested a few decades ago (Christensen, 1995). The results presented in this paper point to confirm gender as another important key factor that is often inadequately taken into consideration when interpreting hair analysis, especially when the metals content is scrutinized according to guidance values computed for the general population. Boys and girls, in fact, exhibit a different behavior with respect to the accumulation/excretion process of metals and metalloids because of difference in their bodily growth, physiology, the presence of specific sexual hormones and metabolizing enzymes, along with lifestyle and physical activity (Vahter et al., 2007). Health effects of some toxic trace elements are also displayed differently between male and female, due to differences in kinetics, mode action, or susceptibility. We found that strontium content in hair is among the most relevant chemical element able to differentiate between male and female. In general females exhibit higher content of Sr than males. Strontium is naturally present almost everywhere in small amounts and humans can be exposed to low levels by inhalation, absorption through the skin and ingestion of food and drinking water. In the human body the behavior of strontium is very similar to that of calcium. Considering that remodeling of bone minerals is responsible for the mobilization of nearly 20% of skeletal calcium (Lindh, 2005), it may be supposed that Sr is involved in the continuous destruction and remodeling of the skeleton structure from which it can be locally dissolved, be taken over by the bloodstream and be eliminated through a preferential expulsion route of metals (urine, feces, sweat, hair). Due to the fact that the growth rate of girls is higher than that of boys it is likely that girls absorb and eliminate faster more strontium than boys (ATSDR, 2004).

th

Mann-Whitney test

75

Coverage interval

Coverage uncertainty (δ)

p-value

7.1 0.05 1.92 0.04 0.15 0.19 22 0.04 0.69 0.07 0.53 1.28 0.01 0.04 0.60 12.0 0.05 0.4 246

1.2-12 0.0003-0.18 0.10-3.6 0.0004-0.28 0.01-0.62 0.001-0.47 7.3-61 0.001-0.25 0.01-5.5 0.0001-0.30 0.04-1.5 0.09-3.7 0.0002-0.15 0.003-0.11 0.08-1.4 0.96-43 0.0001-0.15 0.04-1.6 129-420

0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018

0.002 0.172 b0.001 b0.001 b0.001 0.012 b0.001 0.300 b0.001 0.010 b0.001 0.005 b0.001 0.004 b0.001 b0.001 0.736 b0.001 b0.001

Significantly higher average levels of Sr concentrations in hair of females have been reported by Senofonte et al. (2000) (males 0.90 ± 0.73 μg/g vs females 1.59 ± 1.29 μg/g). Looking at different ages, Rodushkin and Axelsson (2000) reported 0.891 ± 0.731 μg/g in hair of males vs 1.64 ± 1.32 μg/g in females for a population with an average of 32.6 years, whereas Chojnacka et al. (2010a), for a population of 21– 22 years, reported strontium concentration in females 2.5 times higher than in males. Zaichick and Zaichick (2011) asserted that a high content of Sr in hair of women is likely related to differences in the diet with women consuming more plant foods, which is the main supplier of Sr in the human body, than men. Gender-related hair metal concentration difference was also evidenced by Zn levels. The principal source of Zn is the diet. This element is one of the most important essential trace metals present in the human body, covering a plethora of functions in various physiological processes including gene expression, genetic stability, cell growth and division, breakdown of carbohydrates. N300 enzymes have been recognized as depending on zinc for both catalytic and noncatalytic roles (Lindh, 2005; Prasad, 1995; McCall et al., 2000). Interestingly, Dongarrà et al. (2011) reported that Zn, and also Sr, content in hair from triplet children, two girls and a boy presumably having the same type of nutrition, was significantly higher in girls than in boy. Senofonte et al. (2000); Benes et al. (2003); Pereira et al. (2004); Sanna et al. (2008); Barbieri et al. (2011); Carneiro et al. (2011b); Evrenoglou et al. (2013) and Peña-Fernandez et al. (2014) measured Zn concentrations in hair of females from 1 to 2 times higher than in males. Values of Zn 7% higher in females as compared to those found in men were reported by Skalny et al. (2015). Conversely, De Prisco et al. (2010) found 188.52 ± 33.92 μg/g in females with respect to 243.56 ± 153.34 μg/g in males. The observed greater level of Zn in hair of female subjects is due to larger Zn body reserves of young girls, supporting the increased demands of puberty (Heinersdorff and Taylor, 1979). During puberty period, boys and girls, in fact, need high amount of Zn to maintain their skeletal growth and this requirement is more pronounced in girls because of the characteristics of female puberty (Deshpande et al., 2013). Skalny et al. (2015) reported that hair levels of nickel and also strontium were significantly (p b 0.001) higher in women in comparison to the respective values in men. Our results are also in agreement with earlier studies indicating gender-related difference in hair Ni concentrations, as reported by Senofonte et al. (2000); De Prisco et al. (2010);

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Table 2 Descriptive statistical parameters (median, 25th and 75th percentile) and non-parametric Mann–Whitney test, carried out to compare differences in the chemical composition of hair samples (female and male donors) from different sites (industrial areas, polymetallic mining area, urban area and volcanic area). Numbers in bold indicate a statistically significant difference with a p-value less than 0.01; (M) and (F) are referred to male and female subjects, respectively. IA - Samples from industrial areas

Al As Ba Cd Co Cr Cu Li Mn Mo Ni Pb Rb Sb Se Sr U V Zn

PA - Samples from polymetallic mining area

Median (M)

25th (M)

75th (M)

Median (F)

25th (F)

75th (F)

p-value

Median (M)

25th (M)

75th (M)

Median (F)

25th (F)

75th (F)

p-value

5 0.03 0.9 0.01 0.05 0.1 11 0.02 0.4 0.1 0.1 0.8 0.01 0.03 0.5 5 0.04 0.1 188

4 0.02 0.4 0.003 0.02 0.1 10 0.01 0.2 0.04 0.05 0.4 0.01 0.02 0.2 3 0.01 0.1 163

7 0.06 2 0.02 0.11 0.2 14 0.09 0.6 0.1 0.2 1 0.03 0.05 0.6 9 0.06 0.1 212

5 0.04 2 0.01 0.09 0.1 13 0.03 0.6 0.1 0.3 0.5 0.01 0.02 0.4 19 0.03 0.1 203

4 0.02 1 0.005 0.04 0.1 11 0.01 0.3 0.04 0.2 0.3 0.004 0.01 0.2 13 0.02 0.1 181

8 0.07 2 0.02 0.19 0.2 17 0.11 1 0.1 0.6 1 0.01 0.04 0.6 26 0.06 0.2 246

0.596 0.214 b0.001 0.133 b0.001 0.991 b0.001 0.513 b0.001 0.601 b0.001 0.007 b0.001 0.010 0.405 b0.001 0.770 b0.001 b0.001

4 0.04 0.7 0.02 0.03 0.1 12 0.02 0.2 0.03 0.1 0.4 0.01 0.01 0.9 0.8 0.01 0.1 221

3 0.03 0.4 0.01 0.02 0.1 10 0.01 0.1 0.02 0.1 0.3 0.00 0.01 0.7 0.5 0.01 0.1 199

6 0.07 1 0.07 0.06 0.2 15 0.03 0.3 0.04 0.2 1 0.01 0.03 1 2 0.02 0.2 242

4 0.04 1 0.01 0.03 0.1 15 0.01 0.2 0.04 0.2 0.5 0.01 0.01 0.7 2 0.02 0.2 237

3 0.03 0.5 0.004 0.02 0.1 11 0.01 0.1 0.03 0.1 0.2 0.003 0.01 0.6 2 0.01 0.1 214

5 0.06 2 0.21 0.10 0.2 21 0.02 0.3 0.1 0.4 1 0.01 0.02 0.9 3 0.04 0.3 321

0.032 0.519 0.001 0.900 0.058 0.189 0.014 0.085 0.576 0.001 b0.001 0.955 0.584 0.257 0.018 b0.001 b0.001 0.148 0.005

UA - Samples from a large urban area

Al As Ba Cd Co Cr Cu Li Mn Mo Ni Pb Rb Sb Se Sr U V Zn

VA - Samples from a volcanic area

Median (M)

25th (M)

75th (M)

Median (F)

25th (F)

75th (F)

p-value

Median (M)

25th (M)

75th (M)

Median (F)

25th (F)

75th (F)

p-value

0.9 0.0003 0.9 0.02 0.08 0.2 18 0.30 0.2 0.1 0.04 0.8 0.03 0.03 0.4 3 0.03 0.1 132

0.01 0.0003 0.4 0.006 0.04 0.1 13 0.17 0.04 0.0001 0.04 0.6 0.02 0.02 0.3 2 0.01 0.1 123

5 0.002 2 0.04 0.23 0.4 20 0.45 0.3 0.3 0.2 1.3 0.04 0.04 0.6 6 0.05 0.1 144

7 0.0003 1 0.03 0.07 0.1 21 0.02 0.3 0.03 0.6 0.8 0.01 0.01 0.4 8 0.01 0.1 192

6 0.0003 1 0.018 0.03 0.0 16 0.001 0.1 0.01 0.4 0.6 0.0002 0.01 0.3 6 0.003 0.05 173

9 0.01 2 0.07 0.17 0.1 28 0.05 0.5 0.1 0.8 1 0.02 0.03 0.5 9 0.02 0.1 238

b0.001 0.282 b0.001 b0.001 0.485 b0.001 b0.001 b0.001 0.043 0.307 b0.001 0.971 b0.001 b0.001 0.089 b0.001 b0.001 0.278 b0.001

5 0.03 0.8 0.01 0.02 0.1 11 0.01 0.3 0.03 0.1 0.4 0.01 0.02 0.5 0.97 0.03 0.2 196

3 0.01 0.3 0.006 0.01 0.1 9 0.01 0.2 0.01 0.1 0.2 0.006 0.01 0.5 0.4 0.02 0.1 171

6 0.04 1 0.02 0.03 0.2 15 0.02 0.4 0.1 0.3 0.8 0.02 0.04 0.6 2 0.06 0.3 216

5 0.03 0.8 0.02 0.02 0.1 15 0.02 0.4 0.05 0.2 0.8 0.01 0.03 0.5 4 0.04 0.5 205

4 0.01 0.4 0.008 0.01 0.1 11 0.01 0.2 0.02 0.1 0.4 0.006 0.02 0.4 3 0.02 0.3 174

7 0.04 2 0.03 0.07 0.2 22 0.03 0.7 0.1 0.4 1 0.02 0.05 0.6 7 0.08 0.9 235

0.447 0.523 0.074 b0.001 b0.001 0.569 b0.001 0.016 b0.001 b0.001 b0.001 b0.001 0.445 0.049 b0.001 b0.001 0.003 b0.001 b0.001

Michalak et al. (2012); Evrenoglou et al. (2013). At the same time, our data are in contrast to the results obtained by Barbieri et al. (2011) and Peña-Fernández et al. (2014), who found that hair of males contained more nickel than females (females 0.23 ± 4.89 μg/g vs male 0.32 ± 6.5 μg/g and females 0.38 ± 0.34 μg/g vs male 0.58 ± 0.34 μg/ g, respectively). Nickel is an essential nutrient in some body chemical processes although its precise functions remain still largely unknown, but it is also one of the most common causes of allergy (Lindh, 2005) and listed among carcinogenic agents (Nohynek et al., 2004). Kabata-Pendias and Pendias (1999) reported that nickel is accumulated mostly in parenchymal organs, myocardium, bones, skin, and hair. It has been reported that exposure to nickel has recently increased due to its wide use in different fields, such as metallurgical industry for the production of alloys, electroplating, batteries, stainless-steel and in medical engineering where it is employed in the production of tool and dental implants. Other uses include cosmetic and jewelry (ATSDR, 2005; Michalak et al., 2012). The most common sources for children exposure to Ni are food, through consumption of bread cereals, vegetables and beverages, contact with everyday items such as nickel-containing jewelry and breathing ambient air containing nickel released from oil combustion (Nath et al., 2000; Cempel and Nikel, 2006).

5. Conclusions We have considered the profiles of 19 trace elements in scalp hair of children living in different environmental contexts with the aim of evidencing that hair level of some metal and metalloids is distinctively gender specific. The obtained data usefully identified some different distributions with adolescent girls exhibiting significantly higher hair concentrations of some trace metals, especially Sr, Zn and Ni, than boys. Understanding the reasons for these differences was beyond the scope of this work, but the importance of these differences is clear as they may have a significant impact on the application of the common coverage intervals. Gender difference acts as confounding factor and therefore it should be better explored in hair biomonitoring methods. Consequently, coverage intervals established for a general population may not be wholly relevant to particular circumstances. Whenever hair coverage intervals do not adequately address the differences due to gender and also residence site, it is difficult to interpret whether the observed value for the sample is higher or lower than the employed reference level. Concluding, we suggest a) to reflect on the use of existing coverage intervals as unique choice for interpreting laboratory results and b) to promote attainment of coverage intervals reflecting the characteristics of the studied population.

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