Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

Qi Yao; Ge Zhou; Meilin Xu; Jianguo Dai; Ziwei Qian; Zijing Cai; Luyao Zhang; Yong Tan; Rongkui Hu

doi:10.1371/journal.pone.0224892

. 2019 Nov 7;14(11):e0224892. doi: 10.1371/journal.pone.0224892

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

Qi Yao ^1,^#, Ge Zhou ^2,^#, Meilin Xu ³, Jianguo Dai ¹, Ziwei Qian ¹, Zijing Cai ¹, Luyao Zhang ¹, Yong Tan ^2,^*, Rongkui Hu ^2,^*

Editor: Yi Hu⁴

PMCID: PMC6837506 PMID: 31697766

Abstract

Environmental exposure to metals is ubiquitous, but its relation to androgen hormone levels is not well understood, especially in children and adolescents. This study aimed to explore the relationship between blood metal concentrations (lead, cadmium, total mercury, selenium, and manganese) and serum total testosterone (TT) levels in 6–19-year-old children and adolescents in the National Health and Nutrition Examination Survey (NHANES) 2011–2012. Weighted multivariable linear regression models using NHANES sampling weights were employed to evaluate the association between log-transformed serum TT and each metal categories in male and female children (age 6-11years) and adolescents (age 12–19 years). We established that blood cadmium and manganese levels were associated with significantly higher serum TT levels in the female adolescents. Additionally, the blood selenium levels in male adolescents were related to significantly higher serum TT. No significant associations between blood lead or total mercury levels and TT were observed in children or adolescents of either sex. These findings suggest that environmental exposure to certain metals could affect serum TT levels in adolescents, which might have important implications for the health of adolescents. Further research is required to confirm and extend our present findings.

Introduction

Testosterone is a principal sex hormone needed for the normal physiologic processes during all life stages. In males, testosterone is essential for the development and maintenance of secondary sexual traits [1–2]. Testosterone also influences bone mass, muscle strength, mood, and intellectual capacity [1–2]. In females, testosterone is of crucial importance for bone density and is necessary for normal ovarian and sexual function, libido, energy, and cardiovascular and cognitive functions [3–4].

Testosterone imbalances lead to reproductive dysfunction during multiple life stages in both sexes. Low testosterone levels are related to reduced semen quality in men [5, 6], increased genital malformations [7], and changes in the time of onset and/or progression of puberty [8–9]. On the other hand, high testosterone levels are linked to polycystic ovary syndrome (PCOS) in females [10], increased genital system cancers [11, 12], and altered pubertal development [13, 14]. Therefore, research on the factors affecting testosterone levels in both sexes is needed.

Metals have been shown to interact with testosterone levels. The general population is exposed to low concentrations of metals daily through the consumption of water, foods, supplements, and inhalation of air. Due to widespread metal exposure of humans, a growing concern exists regarding their endocrine-disrupting potential. Non-essential metal elements, such as cadmium, lead, and mercury, have endocrine-disrupting properties even at low concentrations. A positive relationship between environmental cadmium exposure and testosterone levels has also been shown among adult males and females [15–20], and several epidemiologic studies have indicated that environmental lead exposure is associated with increased testosterone levels in U.S., Croatian, and Chinese men [21–23].The research regarding environmental mercury exposure and testosterone levels in humans is limited. A study by Barregârd et al. showed that serum total testosterone (TT) concentrations were positively correlated with cumulative mercury exposure [24]. Essential metals, such as manganese and selenium, can be harmful depending on their concentrations. Rats exposed to low manganese levels had increased testosterone levels, while high manganese levels resulted in decreased testosterone levels [25–27]. Exposing adult male rats to low selenium concentrations resulted in increased testosterone levels, while high levels resulted in decreased testosterone levels [28, 29].

In summary, most studies assessing the reproductive endocrine-disrupting effect of low, environmentally-relevant metal exposures in adults have focused on non-essential metals (cadmium and lead), whereas information on other potential endocrine-disrupting metals is still scant. Moreover, children and adolescents are at the ages where susceptibility to the adverse health effects of endocrine disruptors is most concerning. Few studies have focused on the relationship between environmental metal exposure and endogenous androgen hormone levels in children and adolescents. Therefore, our objective was to examine the potential associations between blood metal (cadmium, lead, mercury, manganese, and selenium) and circulating serum TT levels in a general population sampling of 6–11-year-old children and 12–19-year-old adolescents in the United States.

Materials and methods

Study population

We analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011–2012. NHANES is a cross-sectional, U.S.-representative survey conducted annually by the Centers for Disease Control and Prevention (CDC). The goal of NHANES is to assess the health and nutritional status of the general U.S. population. The data were collected by questionnaire surveys, household interviews, physical examinations, and laboratory tests. We analyzed data from a subset of male children (age 6–11 years), male adolescents (age 12–19 years), female children (age 6–11 years), and female adolescents (age 12–19 years). Participants with missing data on blood metal levels, serum TT, and covariates were excluded from the analysis. In the final sample size, we assessed data from 431 male children, 493 male adolescents, 426 female children, and 470 female adolescents. NHANES received approval from the National Center for Health Statistics (NCHS) Ethics Review Board, and informed consent was obtained for all participants.

2.2 Blood sample

Whole venous blood were collected from participants at the Mobile Examination Center (MEC), which were then processed, stored, and shipped to laboratories at the CDC (Atlanta, GA, USA) for analysis. Samples were analyzed for blood metals, serum TT and serum cotinine.

2.3 Serum total testosterone levels

Serum TT levels were analyzed by isotope-dilution liquid chromatography-tandem mass spectrometry. Information regarding the reliability, validation, and quality control of serum TT levels is presented in detail in the NHANES laboratory methods (http://www.cdc.gov/nchs/data/nhanes/nhanes_11_12/TST_G_met.pdf).

2.4 Blood metals

Whole blood lead, cadmium, total mercury, manganese, and selenium concentrations were determined using inductively coupled plasma mass spectrometry-based on quadrupole ICP-MS technology. The methodologic details of blood metal detection and measurements are described in the NHANES laboratory methods(http://www.cdc.gov/nchs/data/nhanes/nhanes_11_12/PbCd_G_met_blood%20metals.pdf). The detection limit for all analytes was constant in the data set. The lower detection limit(LOD) for lead was 0.25 μg/dL, whereas it was 0.16 μg/L for cadmium, 30 μg/L for selenium, 1.06 μg/L for manganese, and 0.16 μg/L for total mercury. Values below the LOD were imputed by LOD and divided by the square root of 2, which provided an imputed value for the individuals who had levels below the LOD.

2.5 Covariates

We examined the following as potential confounding variables: age, race/ethnicity, poverty income ratio (PIR), obesity, seasons of collection, times of venipuncture, and serum cotinine as a biomarker of exposure to environmental tobacco smoke. The selection of these confounders was based on literatures [17, 30].Race/ethnicity was categorized as Non-Hispanic White, Non-Hispanic Black, Hispanic (Mexican American and other Hispanic black), and others. PIR represents the calculated family income to the poverty ratio threshold. Children and adolescents were classified as normal/underweight, overweight, or obese according to their age and sex, in compliance with the criteria defined by NHANES (Body Measures File; https://wwwn.cdc.gov/Nchs/Nhanes/2011-2012/BMX_G.htm). The collection season was obtained from the NHANES demographic data pertaining to the six-month period when the examinations were conducted, which was then classified into two categories, including November 1^st–April 30^th and May 1^st–October 31^st. The time of venipuncture, which can be found in the NHANES Fasting Questionnaire File, was categorized as morning, afternoon, or evening sessions. Serum cotinine was measured with isotope dilution-high performance liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometry (ID HPLC-APCI MS/MS).The methodological details of the detection and measurements of serum cotinine the levels are described in the NHANES laboratory methods (http://www.cdc.gov/nchs/data/nhanes/nhanes_11_12/COT_G_met_cotinine.pdf).

2.6. Statistical analysis

All statistical analyses were performed using Empower (R) (www.empowerstats.com, X&Ysolutions, inc.Boston, MA) and R (http://www.R-project.org) software. Descriptive statistics of participant demographics and concentrations of the metals was calculated. Lead, total mercury, manganese, and selenium were categorized into quartiles because more than 75% of the samples were above LOD. The grouping cut-point for cadmium was determined by the percentage of samples LOD. The low group consisted of all subjects with blood cadmium <LOD, whereas the medium and high groups consisted of equal-sized bins among the detected values. Serum TT was log-transformed for analyses, because the distribution of serum TT was skewed left. Serum cotinine was log-transformed as well. We employed weighted multivariable linear regression models using NHANES sampling weights to evaluate the association between log-transformed serum TT and each metal categories adjusted for the covariates described in section 2.5. Model 1 controlled for age, race and BMI. Model 2 controlled for PIR, seasons of collection, times of venipuncture, and serum cotinine, in addition to the covariates of model 1. Because our dependent variable, serum TT, was log-transformed, the estimated coefficients (β) in the weighted regression models were transformed back by exponentiation of β (exp(β)) and presented as percent differences (equation: % change = [exp(β)-1]× 100). Since the analyses were performed for each subgroup (male children, male adolescents, female children, and female adolescents) separately, the p-values were adjusted for multiple testing using least significant difference (LSD) method. P-values less than 0.05 were considered to be statistically significant.

Results

The characteristics of the study population by age and sex categories are presented in Table 1. The median serum TT levels of male children, male adolescents, female children, and female adolescents were 3.16 ng/dL, 354.67 ng/dL, 4.86 ng/dL, and 23.95 ng/dL, respectively.

Table 1. Characteristics of the 6–19-year-old children and adolescent participants in NHANES 2011–2012.

Parameter	Male children	Male adolescents	Female children	Female adolescents
n	431	493	426	470
Age (years)	9 (7–10)	15(14–17)	9 (7–10)	15(13–17)
Serum total testosterone (ng/dL)	3.16 (1.80–5.68)	354.67(208.08–496.58)	4.86 (2.69–10.29)	23.95 (16.72–31.55)
Serum cotinine (ng/mL)	0.035 (0.011–0.242)	0.038 (0.011–0.431)	0.039 (0.011–0.181)	0.028 (0.011–0.210)
Ratio family income to poverty	1.26(0.74–2.70)	1.57 (0.86–3.40)	1.30 (0.70–2.78)	1.40 (0.69–2.96)
Obesity^a
Normal/underweight	263 (61.02%)	309 (62.68%)	266 (62.44%)	297 (63.19%)
Overweight	66 (15.31%)	77 (15.62%)	68 (15.96%)	76 (16.17%)
Obese	102 (23.67%)	107 (21.70%)	92 (21.60%)	97 (20.64%)
Race/ethnicity
Non-Hispanic White	113 (26.22%)	119 (24.14%)	98(23.01%)	105 (22.34%)
Non-Hispanic black	116 (26.91%)	154 (31.24%)	128(30.05%)	141 (30.00%)
Hispanic	145 (33.64%)	138 (27.99%)	129(30.28%)	144 (30.64%)
Other	57 (13.23%)	82 (16.63%)	71(16.67%)	80 (17.02%)
Session time of venipuncture
Morning	177 (41.07%)	243 (49.29%)	207 (48.59%)	237 (50.43%)
Afternoon	157 (36.43%)	170 (34.48%)	149 (34.98%)	156 (33.19%)
Evening	97 (22.51%)	80 (16.23%)	70 (16.43%)	77 (16.38%)
Six-month period when the examination was performed
1 November through 30 April	216 (50.12%)	237 (48.29%)	221 (51.88%)	216 (45.96%)
1 May through 31 October	215 (49.88%)	256 (51.93%)	205 (48.12%)	254 (54.04%)

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Data are summarized as median (interquartile range) for continuous variables or as number with proportion for categorical variables.

^aChildren and adolescents were classified as normal/underweight, overweight, or obese according to their age and sex, as defined by NHANES (http:/wwwn.cdc.gov/Nchs/Nhanes/2011-2012/BMX_G.htm)

As can be seen in Table 2, which shows the distribution of blood metals concentrations by age and sex categories, blood manganese and selenium levels were >LOD for all samples. >75% of the samples had blood lead and total mercury levels >LOD in children and adolescents. 27.8% of the samples had blood cadmium levels >LOD in male children.35.0% of the samples had blood cadmium levels >LOD in female children.51.9% of the samples had blood cadmium levels >LOD in male adolescents.58.7%% of the samples had blood cadmium levels >LOD in female adolescents.

Table 2. The distribution of metal concentrations in the blood of the 6–19-year-old children and adolescent participants in NHANES 2011–2012.

Parameter	Male children				Male adolescents
n	431				493
	N(%)<LOD	Geometric	median	interquartile	N(%)<LOD	Geometric	median	interquartile
Blood lead (μg/dL)	7 (1.6%)	0.76	0.72	0.52–1.02	11 (2.2%)	0.68	0.66	0.47–0.96
Blood cadmium (μg/L)	311 (72.2%)	0.13	0.11	0.11–0.16	237 (48.1%)	0.17	0.16	0.11–0.23
Blood mercury, total (μg/L)	69 (16.0%)	0.35	0.34	0.20–0.59	48 (9.7%)	0.47	0.43	0.23–0.79
Blood selenium (μg/L)	0 (0.0%)	174	175	163–188	0 (0.0%)	187	187	174–202
Blood manganese (μg/L)	0 (0.0%)	9.79	9.72	7.86–11.84	0 (0.0%)	9.43	9.33	7.62–11.54
Parameter	Female children				Female adolescents
n	426				470
	N(%)<LOD	Geometric	median	interquartile	N(%)<LOD	Geometric	median	interquartile
Blood lead (μg/L)	6 (1.4%)	0.68	0.65	0.48–0.93	27 (5.8%)	0.47	0.47	0.35–0.63
Blood cadmium (μg/L)	277 (65.0%)	0.14	0.11	0.11–0.18	194 (41.3%)	0.19	0.18	0.11–0.27
Blood mercury, total (μg/L)	61 (14.3%)	0.39	0.36	0.22–0.66	40 (8.5%)	0.50	0.49	0.26–0.83
Blood selenium (μg/L)	0 (0.0%)	177	177	165–189	0 (0.0%)	184	183	169–200
Blood manganese (μg/L)	0 (0.0%)	10.55	10.52	8.72–12.90	0 (0.0%)	10.75	10.84	8.64–13.26

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Abbreviations: LOD, limit of detection

In female adolescents, serum TT was significantly higher for girls in the 4th vs. 1st quartile of lead exposure, but there were no significant trends with increasing quartiles of exposure (adjusted p-trend = 0.14, based on model 1). Blood lead levels did not appear to be associated with serum TT concentrations in male and female children and male adolescents, and consistent trends with increasing quartiles of exposure were not evident (Table 3).

Table 3. Percent differences (95% CI) in the serum TT by quartiles of blood lead exposure, NHANES, 2011–2012using weighted regression models.

Blood lead(μg/dL)	Model 1^a	Model2^b
Male children(N = 431)
≤0.52(n = 110)	Reference	Reference
0.52–0.72(n = 111)	4.1 (-18.47, 32.9)	11.75(-13.06,43.65)
0.72–1.02 (n = 105)	-6.13(-27.64, 21.77)	-4.63(-26.97, 24.55)
>1.02 (n = 105)	-12.83 (-33.68, 14.58)	-13.09 (-34.45,15.22)
Adjusted p-trend	0.36	0.42
Male adolescents(N = 493)
≤0.47(n = 129)	Reference	Reference
0.47–0.66 (n = 120)	-3.36 (-20.98,18.2)	-4.35 (-21.22,16.14)
0.66–0.96 (n = 121)	14.99 (-7.77,43.37)	8.15 (-12.91,34.3)
>0.96 (n = 123)	15.62 (-7.07,43.86)	6.32 (-14.62,32.4)
Adjusted p-trend	0.18	0.58
Female children(N = 426)
≤0.48(n = 109)	Reference	Reference
0.48–0.65 (n = 106)	14.34 (-3.75,35.81)	14.9 (-3.54,36.86)
0.65–0.93 (n = 106)	-5.00 (-21.05,14.32)	-0.96 (-17.80,19.34)
>0.93 (n = 105)	-5.73 (-23.13,15.61)	-2.40 (-21.00,20.57)
Adjusted p-trend	0.36	0.63
Female adolescents(N = 470)
≤0.35 (n = 122)	Reference	Reference
0.35–0.47 (n = 118)	-8.55 (-18.52,2.63)	-7.83 (-18.22,3.88)
0.47–0.63 (n = 113)	-1.95 (-13.04,10.56)	-1.07 (-12.67,12.06)
>0.63 (n = 117)	13.12 (0.06,27.88)	14.85 (0.83,30.81)
Adjusted p-trend^c	0.14	0.08

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^aAdjusted for age (continuous), BMI (normal/underweight, overweight, and obese) and race-ethnicity (Non-Hispanic White, Non-Hispanic black, Hispanic, and other).

^b Adjusted for variables in model 1 plus serum cotinine (log-transformed, continuous), time of venipuncture (morning, afternoon, and evening), season of collection (1 November through 30 April, 1 May through 31 October), ratio family income to poverty (continuous).

c Adjusted p-trend:p-values adjusted for multiple testing.

As can be observed in Table 4, serum TT concentrations were positively associated with blood cadmium in female adolescents, and a monotonic increase was seen in the mean serum TT concentration with increasing exposure (adjusted p-trend = 0.004, based on model 1). Significantly higher serum TT levels for the 2nd and 3rd blood cadmium exposure levels (13.24%; 95% CI:3.41%, 24.00%, and 23.15%; 95% CI:6.43%, 42.5%, respectively, based on model 1) compared with the lowest exposure levels were also seen. This pattern of association persisted following an adjustment for age, BMI, race, serum cotinine, time of venipuncture, collection season, family income to poverty ratio, and the p-trend remained significant (adjusted p-trend = 0.002, based on model 2). In male adolescents, serum TT levels were significantly higher in boys in the 3rd vs.1st levels of lead exposure, and the trending p-value was significant (adjusted p-trend = 0.04, based on model1). However, the associations were not significant after adjustment for age, BMI, race, serum cotinine, time of venipuncture, collection season, family income to poverty ratio (adjusted p-trend = 0.62, based on model 2). Blood cadmium did not appear to be associated with serum TT concentrations in male and female children, and consistent trends with increasing exposure were not evident.

Table 4. Percent differences (95% CI) in serum TT betweenthree blood cadmium exposure levels, NHANES, 2011–2012using weighted regression models.

Blood cadmium(μg/L)	Model 1^a	Model2^b
Male children(N = 431)
≤0.11 (n = 311)	Reference	Reference
0.11–0.20 (n = 73)	6.87 (-16.33,36.51)	17.65 (-8.02,50.47)
>0.20 (n = 47)	-14.39 (-39.09,20.3)	-8.04 (-34.62,29.35)
Adjusted p-trend	0.86	0.83
Male adolescents(N = 493)
≤0.11 (n = 237)	Reference	Reference
0.11–0.23 (n = 206)	11.31 (-5.45,31.05)	3.56 (-11.68,21.43)
>0.23 (n = 50)	37.97 (4.45,82.26)	21.68 (-11.70,67.68)
Adjusted p-trend	0.04	0.62
Female children(N = 426)
≤0.11 (n = 227)	Reference	Reference
0.11–0.20 (n = 91)	16.19 (-1.16,36.59)	18.24 (0.6,38.98)
>0.20 (n = 58)	-7.95 (-25.67,13.99)	-8.64 (-26.22,13.13)
Adjusted p-trend	0.86	0.83
Female adolescent(N = 470)
≤0.11 (n = 194)	Reference	Reference
0.11–0.25 (n = 200)	13.24 (3.41,24)	14.28 (4.31,25.19)
>0.25 (n = 76)	23.15 (6.43,42.5)	30.79 (9.7,55.94)
Adjusted p-trend^c	0.0038	0.0015

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^a Adjusted for age (continuous), BMI (normal/underweight, overweight, and obese) and race-ethnicity (Non-Hispanic White, Non-Hispanic black, Hispanic and other).

c Adjusted p-trend:p-values adjusted for multiple testing.

In female children, serum TT was significantly higher for girls in the 4thvs.1st quartile of mercury exposure, but there were no signficant trends with increasing quartiles of exposure (adjusted p-trend = 0.10, based on model 1). Blood mercury did not appear to be associated with serum TT in male and female adolescent and male children, and no evidence of consistent trends with increasing quartiles of exposure was established(Table 5).

Table 5. Percent differences (95% CI) in serum TT by quartiles of blood mercury exposure, NHANES, 2011–2012using weighted regression models.

Blood mercury(μg/L)	Model 1^a	Model2^b
Male children(N = 431)
≤0.20 (n = 112)	Reference	Reference
0.20–0.34 (n = 105)	2.45 (-20.36,31.79)	5.49 (-17.59,35.03)
0.34–0.59 (n = 111)	15.02 (-10.17,47.28)	10.29 (-13.62,40.82)
>0.59 (n = 103)	4.92 (-21.02,39.40)	0.67 (-24.36,33.99)
Adjusted p-trend	0.46	0.75
Male adolescents(N = 493)
≤0.23 (n = 125)	Reference	Reference
0.23–0.43 (n = 123)	18.47 (-3.05,44.76)	13.75 (-6.45,38.32)
0.43–0.79 (n = 123)	-10.63 (-28.14,11.14)	-8.68 (-26.14,12.91)
>0.79 (n = 122)	21.77 (-2.77,52.5)	19.28 (-4.21,48.55)
Adjustedp-trend	0.46	0.70
Female children(N = 426)
≤0.22(n = 114)	Reference	Reference
0.22–0.36 (n = 103)	6.76 (-10.22,26.94)	8.62 (-9.17,29.89)
0.36–0.66 (n = 106)	0.89 (-15.07,19.83)	0.7 (-15.56,20.09)
>0.66 (n = 103)	29.78 (7.96,56.00)	29.15 (6.9,56.02)
Adjustedp-trend	0.10	0.14
Female adolescent(N = 470)
≤0.26 (n = 120)	Reference	Reference
0.26–0.49 (n = 118)	-4.72 (-14.67,6.39)	-2.75 (-13.25,9.03)
0.49–0.83 (n = 116)	-2.45 (-13.49,10.00)	0.05 (-11.56,13.17)
>0.83 (n = 116)	-8.28 (-19.6,4.64)	-5.84 (-17.78,7.83)
Adjustedp-trend^c	0.46	0.70

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^a Adjusted for age (continuous), BMI(normal/underweight, overweight, and obese)and race-ethnicity(Non-Hispanic

White, Non-Hispanic black, Hispanic and other).

^b Adjusted for variables in model 1 plus serum cotinine (log-transformed, continuous), time of venipuncture (morning, afternoon and evening), season of collection(1 November through 30 April, 1 May through 31 October), ratio family income to poverty (continuous).

c Adjusted p-trend:p-values adjusted for multiple testing.

In male adolescent subjects, the mean serum TT level was higher for boys in the 3rd and 4th quartiles of blood selenium versus those in the 1st quartile, and the trend p-value was significant (adjusted p-trend = 0.0002, based on model 1) (Table 6). However, the quartile-specific increase was significant only for the 4th quartile (43.27%; 95% CI:14.20%, 79.73%, based on model 1). The association were generally consistent with model1 after adjustment for age, BMI, race, serum cotinine, time of venipuncture, season of collection, ratio family income to poverty, and the p-trend remained significant(adjusted p-trend = 0.003 based on model 2). Blood selenium did not appear to be associated with the serum TT level in male and female children and female adolescents, and no evidence of consistent trends with increasing quartiles of exposure was established.

Table 6. Percent differences (95% CI) in serum TT by quartiles of blood selenium exposure, NHANES, 2011–2012using weighted regression models.

Blood selenium(μg/L)	Model 1^a	Model2^b
Male children(N = 431)
≤163 (n = 108)	Reference	Reference
163–175 (n = 109)	-4.76 (-27.11,24.45)	-2.05 (-24.7,27.41)
175–188 (n = 107)	-16.69 (-36.08,8.58)	-13.07 (-32.96,12.71)
>188 (n = 107)	-11.75 (-32.55,15.46)	-8.28 (-29.53,19.37)
Adjusted p-trend	0.32	0.37
Male adolescents(N = 493)
≤174 (n = 126)	Reference	Reference
174–187 (n = 121)	-17.49 (-34.47,3.91)	-18.3 (-34.67,2.16)
187–202 (n = 123)	2.33 (-18.44,28.39)	-4.98 (-23.91,18.67)
>202 (n = 123)	43.27 (14.2,79.73)	33.38 (6.99,66.29)
Adjusted p-trend	0.0002	0.0027
Female children(N = 426)
≤165 (n = 107)	Reference	Reference
165–177 (n = 106)	-16.76 (-30.82,0.18)	-17.64 (-31.6,-0.83)
177–189 (n = 107)	-17.62 (-31.59,-0.80)	-21.52 (-35.01,-5.22)
>189 (n = 106)	-8.78 (-23.63,8.96)	-11.93 (-26.47,5.49)
Adjusted p-trend	0.36	0.23
Female adolescents(N = 470)
≤169 (n = 118)	Reference	Reference
169–183 (n = 117)	4.68 (-7.33,18.25)	4.55 (-7.51,18.19)
183–200 (n = 118)	-6.45 (-16.98,5.41)	-7.79 (-18.3,4.08)
>200 (n = 117)	-7.93 (-18.29,3.75)	-8.23 (-18.56,3.42)
Adjusted p-trend^c	0.13	0.10

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^a Adjusted for age (continuous), BMI (normal/underweight, overweight, and obese) and race-ethnicity (Non-Hispanic White, Non-Hispanic black, Hispanic, and other).

c Adjusted p-trend:p-values adjusted for multiple testing.

As seen in Table 7, according to model 1, TT was significantly higher in all quartiles of blood manganese than in the lowest quartile in all population subgroups of female adolescents. The trend p-value was significant for female adolescents (adjusted p-trend = 0.001, based on model 1). After adjustment for age, the values of BMI, race, serum cotinine, time of venipuncture, season of collection, ratio of family income to poverty, and the p-trend remained significant (adjusted p-trend = 0.0008, based on model 2). No significant associations were found between serum TT and blood manganese levels in male and female children and male adolescents, and no evidence of consistent trends with increasing quartiles exposure was established.

Table 7. Percent differences (95% CI) in serum TT by quartiles of blood manganese exposure, NHANES, 2011–2012using weighted regression models.

Blood Manganese(μg/L)	Model 1^a	Model2^b
Male children(N = 431)
≤7.86 (n = 108)	Reference	Reference
7.86–9.72 (n = 108)	18.17 (-9.85,54.91)	16.09 (-10.90,51.24)
9.72–11.84 (n = 108)	47.31 (13.23,91.66)	48.55 (14.80,92.22)
>11.84 (n = 107)	12.24 (-14.41,47.20)	10.72 (-15.09,44.38)
Adjusted p-trend	0.40	0.46
Male adolescents(N = 493)
≤7.62 (n = 124)	Reference	Reference
7.62–9.33 (n = 124)	38.64 (11.7,72.06)	31.51 (6.78,61.96)
9.33–11.54 (n = 123)	25.2 (0.38,56.16)	15.49 (-6.81,43.13)
>11.54 (n = 122)	18.39 (-5.89,48.94)	11.88 (-10.38,39.68)
Adjusted p-trend	0.40	0.60
Female children(N = 426)
≤8.72 (n = 107)	Reference	Reference
8.72–10.52 (n = 107)	-19.44 (-33.33,-2.65)	-21.3 (-34.91,-4.85)
10.52–12.90 (n = 107)	-4.94 (-21.88,15.68)	-6.5 (-23.13,13.72)
>12.90 (n = 105)	-1.51 (-19.36,20.29)	-3.71 (-21.25,17.72)
Adjusted p-trend	0.49	0.60
Female adolescents(N = 470)
≤8.64 (n = 119)	Reference	Reference
8.64–10.84 (n = 116)	23.04 (8.64,39.36)	22.53 (7.98,39.04)
10.84–13.26 (n = 118)	34.59 (19.41,51.71)	36.26 (20.72,53.81)
>13.26 (n = 117)	24.96 (10.47,41.36)	24.81 (10.31,41.23)
Adjusted p-trend^c	0.001	0.0008

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^a Adjusted for age (continuous), BMI (normal/underweight, overweight, and obese) and race-ethnicity (Non-Hispanic White, Non-Hispanic black, Hispanic, and other).

c Adjusted p-trend:p-values adjusted for multiple testing.

Discussion

The aim of this study was to investigate the associations between blood metal (lead, cadmium, total mercury, manganese, and selenium) and serum TT levels in male and female children and adolescents. In the present cross-sectional analysis of data from NHANES 2011–2012, blood cadmium and manganese levels were positively associated with serum TT levels in female adolescents. Additionally, blood selenium was positively associated with serum TT levels in male adolescents. No significant associations were observed in the children (male or female).

Circulating testosterone in the body includes sex hormone-binding globulin (SHGB)-bound testosterone, albumin-bound testosterone, corticosteroid-binding globulin (CBG)-bound testosterone, and in an unbound or free form. SHBG-bound testosterone is tightly bound and unavailable to cells. Albumin-bound testosterone and CGB-bound testosterone are weekly bound and dissociate from testosterone rapidly [31]. The term bioavailable testosterone refers to the sum of the albumin-bound, CGB-bound, and free components, which represents the testosterone fraction available to cells. In the present study, we evaluated serum TT, which included both the bioavailable and SHGB-bound forms.

Lead and cadmium, as well-known reproductive toxicants and endocrine disruptor compounds, can cause Leydig cell damage and/or hormone imbalances. In vivo and in vitro studies showed that lead and cadmium might directly affect Leydig cell function by impairing steroidogenesis[32–36].Lead and cadmium also might disrupt hypothalamic-pituitary-testicular axis function, which would alter the hormonal milieu[37–40]. In the present investigation, we were unable to establish an association between blood lead or cadmium levels and serum TT levels among children and adolescent males, which suggested that current exposure levels in our population did not adversely affect testosterone synthesis and regulation.

To our best knowledge, this is the first study to look at the relationships between cadmium exposure and circulating TT levels in adolescent female subjects. The positive association between cadmium and TT levels in female adolescents found in this study was in agreement with the findings reported by Ali I et al. [16] and Nagata C et al. [19]. Ali I et al investigated the relationship between blood cadmium exposure and serum sex hormone levels in 438 postmenopausal Swedish women without hormone replacement therapy, a positive association between blood cadmium and serum TT levels, and an inverse association between blood cadmium and serum estradiol levels and the estradiol/testosterone ratio was found [16]. It is possible that cadmium with LH-induced P450 aromatase activity was responsible for the conversion of testosterone to estradiol. Das and Mukherjee showed that LH-stimulated P450 aromatase activity and P450arom gene expression in carp ovarian follicles were significantly inhibited by cadmium chloride (CdCl₂) [41].Unfortunately, gonadotropins and estradiol were not measured in the 2011–2012 NHANES survey. Nagata C et al. found a significantly positive relationship between urinary cadmium and serum TT levels in 164 postmenopausal Japanese women [19]. In a study on rats, exposure to either moderate or high doses of dietary cadmium during gestation led to an increase in serum TT levels in the female rat offspring[42].

We observed a significant positive association between blood manganese and serum TT levels in female adolescents, whereas no association between blood manganese and serum TT levels was found in male adolescents. Several animal studies as reviewed by Dees [43], showed that exposing female and male rat pups to low but increased manganese levels caused the release of hypothalamic luteinizing hormone-releasing hormone (LHRH) in the serum of animals. This effect of manganese on the LHRH-releasing system was consistent with the elevated serum LH, FSH, and gonadal steroid levels in both sexes. Interestingly, sex differences were also observed; males required a higher manganese dose to influence the hypothalamic system compared with females, which indicated that male hypothalamic systems were less sensitive to the influences of manganese. The reason for these sex differences might be due to diversities in the manganese metabolism between the two sexes since male rats can clear the metal over twice faster than females [44].

We also observed a significant positive association between blood selenium and serum TT levels in male adolescents. Selenium is an essential trace element required primarily for the maintenance of spermatogenesis and male fertility [45]. In previous studies, appropriate selenium levels appeared to exert a positive influence on Leydig cells, which thus influenced the secretion of testosterone [46]. An epidemiologic study also revealed that serum TT tended to increase in infertile men supplemented with selenium [47].

Certain limitations of the present study should be acknowledged. First, NHANES is a survey with a cross-sectional design, which restricts the proper interpretation of the causal associations between metal exposures and serum TT levels. Second, no data on free testosterone, SHBG, or other hormones or markers that might have provided clues regarding the mechanisms and/or sites of action of blood metals, were available. Third, the group of 12-to-19-year-old boys and girls classified as adolescents could have included a mixture of pre- and postpubescent children. Lastly, there might have been other confounding factors that we did not evaluate in our analysis.

Conclusions

The results from this study suggest that the blood levels of certain metals were associated with altered serum TT concentrations in male and female adolescents, included in NHANES 2011–2012 data. Our findings pertain to low-level environmental metals exposure and might not be generalizable to environmental or occupational settings where higher metal doses could be encountered. Additionally, altered T levels were found to be linked to a wide range of adverse health effects, but additional epidemiologic human studies, as well as mechanistic studies, are needed to confirm the results of our analysis.

Supporting information

S1 File. Data name related to this study can be found in S1 File.

(XLS)

Click here for additional data file.^{(43.5KB, xls)}

S2 File. Data related to this study can be found in S2 File.

(XLS)

Click here for additional data file.^{(3.2MB, xls)}

Acknowledgments

We are grateful for the editors and reviewers.

Data Availability

All relevant data are within its Supporting Information files.

Funding Statement

This work was supported by grants from the National Natural Science Fund for Young Scholars (Grant No. 81704164), Natural Science Foundation of the Jiangsu Province (Grant No. BK20151043), Six Talent Peaks Project in the Jiangsu Province (Grant No. WSN-044), and 333 Talent Project in the Jiangsu Province (Grant No. 2016Ⅲ-3288). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0224892.r001

Decision Letter 0

Yi Hu

15 Jul 2019

PONE-D-19-17206

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

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Reviewer #1: Dear Editor,

Thank you for the opportunity to provide a review of Manuscript PONE-D-19-17206, a research article entitled “Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012.” My comments relate primarily to the adequacy of the implementation and reporting of epidemiologic and statistical procedures.

The quality of the technical English was generally appropriate, but there are a number of errors in the text. The manuscript requires a thorough round of copyediting review. Nevertheless, the errors offered no bar to the clear assessment of the issues in the manuscript.

There are three major issues in this manuscript:

1. The authors need to justify their decision to ignore the use of sampling weights arising from the complex survey design of the NHANES. The justifications they provide -- accounting for the design effect is inefficient, that accounting for the oversampling in statistical models is appropriate, and that these technqiues have been used by others before -- is inadequate. First, the argument that others’ methods are applicable here is specious. There is no *positive* evidence that research is similar to the others. The danger of blindly following others is well known. Second, the inefficiency of the design effect and consideration of oversampling via statistical models stem from a serious misunderstanding of the paper by Korn and Graubard (appearing as reference 28 in the manuscript). I suggest that the authors study this paper carefully. It is my recommendation that the authors:

1. provide direct evidence that the use of their unweighted analysis meets the strict assumptions described by Korn and Graubard;

2. conduct weighted, unweighted and partially weighted analyses to determine the amount of inefficiency;

3. using the information from (a) and (b) above, provide clear and specific descriptions of the approach they will take.

I am not prepared to accept justification stemming from an erroneous understanding of the advice provided by Korn and Graubard that has then been adopted by other researchers as *carte blanche* permission to ignore the complex sampling design of the NHANES.

2. The authors have used a very crude method to approximate the level of heavy metal concentration when it is below the level of detection. They’re imputing a single value -- detection limit divided by the square root of two. This has the effect of reducing variability substantially, especially for cadmium. The detection limit is a hard limit. That is to say, replacing this limit with a single number only shifts the limit, but does not resolve the presence of a limit. For example, the limit for cadmium is reported by the authors to be 0.16 micrograms per litre. Table 2 shows that 72.2% of male children had levels below this limit. Thus, for these children, the limit was replaced with an imputed value of 0.16/sqrt(2) = 0.113. As I described, this simply shifted the original lower limit. The decision to do this means that the standard errors have been deflated, causing spurious reductions in the p-value. The authors need to consider more sophisticated techniques, possible through regression methods, that can resolve this. (In this setting, the data are termed “left truncated”.)

3. The authors have performed multiple testing on the same data and their results need to be considered quite carefully because it might be a chance finding. Let me demonstrate. The authors tested five metals (Cd, Pb, Hg, Mn, Se) on four groups (male children, female children, male adolescents, female adolescents) under three models (model 1 and model 2 and test for trend). Thus, the number of independent analyses conducted on the data is 5 x 4 x 3 = 60. That they have found about eight statistically significant results is hardly surprising, especially when they were not expecting these results in the first place. I strongly recommend that the authors adjust the familywise error rate.

The combined effect of the three issues above imply that the presence of biased inferences is quite likely. These three issues must be resolved with urgency. Until then, it is difficult to give credence to the results, discussion and conclusions of the paper, as these might change substantially.

Finally, to my mind, the more important issue here is not the degree to which heavy metals affect the level of testosterone, but whether these levels are associated with levels that are in the range for clinical action. The important *clinical* question is whether heavy metal concentrations are related to clinical testosterone deficiency in children and adolescents.

I am unwilling to recommend the acceptance of this manuscript until such time as these issues are considered.

Reviewer #2: All required questions have been answered and that all responses meet formating specifications.

Comments:

1. General comments: Define all abbreviations the first time they are used. Abbreviations defined in the abstract should be redefined in the body of the manuscript.

2. The abbreviation for serum TT levels is not consistent throughout the manuscript,

3. There are many details are needed, For an example on the introduction and discussion include reference to many studies for which the model studied (human, rats, mice) is not identified and the route of exposure is not provided.

4. In the “Introduction and Discussion” section There are repetition in many paragraphs. Please avoid redundancies

5. In the “Discussion” section the authors need to explain the significance of their findings and the novelty of their study and should substantiate their findings with already available relevant scientific information.

6. Discussion is too long , hard to follow and could be better organized.

7. In the “Discussion” section 1 st paragraph ( line7). Please correct levers to levels

8. Parts of the Discussion section are particularly hard to understand. Professional assistance is recommended.

9. In result caption section . Table 2. please add table legand blew the table

Reviewer #3: The manuscript describes the data taken on metals levels in blood and their association with testosterone levels in children and adolescents. The authors have successfully correlated two metals concentrations (Cd and Mn) with testosterone concentrations in the subjects, highlighting the fact that environmental exposure to heavy metals may lead to altered testosterone levels in growing children. Overall the manuscript describes interesting findings, which are important to publish.

However, I have few questions in mind while reading this manuscript for review purpose, which the authors need to answer before the manuscript is accepted for publication

Reviewer #4: General comment

The aim of this study is to investigate the association between blood levels of metals/elements and serum levels of testosterone in US children and adolescents. This study is new due to the research of association between metals and testosterone in children and adolescent is scarce. The methods align with the study aim and design is acceptable. The article is written in standard English. The conclusions are presented appropriately and are supported by the data.

However, the description of methods and result is not comprehensive. Revision is necessary before further consideration.

Specific comments

Introduction:

More description of previous epidemiologic studies regarding the correlation of metals such as lead, mercury, manganese, selenium and levels of androgen hormones is necessary.

It is also necessary to give clear description of total testosterone (TT). Were serum T or serum TT levels given in the cited epidemiological studies? In the manuscript, sometimes serum T is given while sometimes serum TT is given. Please make these term clear.

At page 3, 3rd paragraph, the cited animal studies of Cd and Hg are not related to androgen hormone levels, more relevant literature is needed.

Material and Methods: full name of NCHS, LOD should be given.

Page 5, 2.2 Serum TT: information of blood sampling should be given, were the blood samples for serum TT collected at the same time point as blood samples of metals?

Page 5, last two lines at the bottom: sentence “ Serum TT was log-transformed… was skewed left.” should be in the Statistical Analysis section.

Page 6, 2.4 Covariates: what is the reason to choose these confounding variables? Is the selection of confounders based on literature or Directed Acyclic Graph (DAG) or other methods?

Page 7, line 1-2: Please give the explanation for “we combined underweight and normal weight in one category”. What is the background to do so?

Page 7, line 7: please give a short description of serum cotinine measurement. Sentence “ serum cotinine was log-transformed” should be in the Statistical Analysis section.

Page 7, Statistical Analysis:

The statistical power of category variables is generally weaker than continuous variables. For the association analysis of blood levels of metals and serum TT concentrations, authors only performed the linear regression analysis using quartiles and tertiles of metals while not run analysis for continuous metal data. Please clarify it.

In the Table 3-7, Model 1 and Model 2 are given. However, the description of Model 1 and Model 2 is not given here. Please clarify why use these two models and give the corresponding description in Statistical analysis section.

Results

Page 8, Line 2 -3 under Results: for sentence “ As expected, serum TT concentrations…. than male children.” Are the differences statistically significant? Are there significant differences of serum TT between female children and female adolescent? In addition, are there difference between genders and between children and adolescent for other characteristics parameters?

Page 8, line 3 from bottom: sentence “ A large portion (98.6%-84.0%) of the samples had blood lead and total mercury levels > LOD” is not clear. This sentence should be reformulated to separately describe lead and mercury.

Page 8, last line: sentence “ The median concentrations of all blood metals were higher in adolescents than in children. Are the differences statistically significant?

Page 10, line 6-8: sentence “ The mean serum TT was significantly lower for all quartiles of blood selenium than that of the lowest quartile in all population subgroups.” is not precise. This is the case only for female children. Please check!

Page 10, line 1-2 of last paragraph: sentence “ As seen in Table 7…. in all population subgroups” is not precise. This is the case only for female adolescents. Check!

Discussion: beware of “serum T” and “serum TT”. Are they same term?

Page11, line 2-6 of 2nd paragraph: sentences “ In a previous study, Meeker et al…. which is in contrast to the results of the present study.” is not clear. Did Meeker measure serum TT or serum T? What is the difference between serum T and serum TT in these sentences? Serum T is free testosterone?

Page 12, line 8-13: for sentences “ Differences in cadmium or lead levels…. in children and adolescent males, respectively”, it is doubtful to compare the present study with the cited studies (reference 32, 33) which were for adults while the present study is for children and adolescent because the level of both metals and androgens are different for adults and children, adolescents.

Page 15, line 2-3: sentence “ Our findings… may not be generalizable to environmental .. “ is not clear. Reformulation is necessary.

Table 3-7: sample numbers of each quartile or tertile should be given in the tables.

Supporting information is not mentioned in the text. What is the aim by giving this information?

Reviewer #5: The manuscript entitled "Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011-2012"aimed to investigate whether there is an association between exposure to heavy metals and testosterone levels in children and adolescents. The work was well conducted, presents a relevant sample population and the results were explored through a consistent statistical analysis. The results indicated that some blood metals were positively associated with serum TT levels in female and male adolescents. However, the introduction of the article does not value the importance of the study. Much of the introduction (page 4, line 3-17) contains elements that are also cited in the discussion. Alternatively, the authors should explore in the introduction what are the sources or means of exposure of each of the heavy metals studied, as well as problematize how this exposure can impact the health of this specific population. Thus, I suggest that the authors make a comprehensive review of the introduction of the manuscript. In addition, a general review of writing is recommended, as several spelling errors were found throughout the text.

**********

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Reviewer #2: No

Reviewer #3: Yes: Dr. Tariq Mahmood

Reviewer #4: No

Reviewer #5: Yes: Fernanda Cristina Alcantara dos Santos

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PLoS One. 2019 Nov 7;14(11):e0224892. doi: 10.1371/journal.pone.0224892.r002

Author response to Decision Letter 0

23 Sep 2019

Dear editor:

Thank you very much for your letter and the reviewers' comments. We have carefully studied the comments of the reviewers and made corrections accordingly, which are highlighted in red in the revised version of the manuscript. Point-by-point responses are listed below. We hope that revised version is acceptable for publication in your journal. I am looking forward to hearing from you.

Sincerely Yours,

Rongkui Hu, M.M.

Department of Reproductive Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, 155 Hanzhong Road, Nanjing, 210046, Jiangsu Province, China.

E-mail: xiangyu198110@163.com

Responses to the reviewers

First of all, we sincerely thank all reviewers for their positive and constructive comments and suggestions, which not only help improve our manuscript, but also provide some ideas for our future studies. We have carefully studied the comments of the reviewers and made corrections accordingly, which are highlighted in red in the revised version of the manuscript. Point-by-point responses are listed below.

Reviewer #1:

Response to comment: The authors need to justify their decision to ignore the use of sampling weights arising from the complex survey design of the NHANES. The justifications they provide -- accounting for the design effect is inefficient, that accounting for the oversampling in statistical models is appropriate, and that these technqiues have been used by others before -- is inadequate. First, the argument that others’ methods are applicable here is specious. There is no *positive* evidence that research is similar to the others. The danger of blindly following others is well known. Second, the inefficiency of the design effect and consideration of oversampling via statistical models stem from a serious misunderstanding of the paper by Korn and Graubard (appearing as reference 28 in the manuscript). I suggest that the authors study this paper carefully. It is my recommendation that the authors:

1. provide direct evidence that the use of their unweighted analysis meets the strict assumptions described by Korn and Graubard;

2. conduct weighted, unweighted and partially weighted analyses to determine the amount of inefficiency;

3. using the information from (a) and (b) above, provide clear and specific descriptions of the approach they will take.

Response: We appreciate the reviewer’s thoughtful comments. This is absolutely right. Sampling weights are critical in this complex survey design of NHANES. We rechecked the data and literatures and decided to use weighted analyses as the reviewer suggested. Details of the approach were described in the ‘Statistical Analysis’ section. The tables, results and conclusions were updated accordingly. We thank the reviewer again for this constructive comment, which helped us improve the quality of the manuscript.

Response to comment: The authors have used a very crude method to approximate the level of heavy metal concentration when it is below the level of detection. They’re imputing a single value -- detection limit divided by the square root of two. This has the effect of reducing variability substantially, especially for cadmium. The detection limit is a hard limit. That is to say, replacing this limit with a single number only shifts the limit, but does not resolve the presence of a limit. For example, the limit for cadmium is reported by the authors to be 0.16 micrograms per litre. Table 2 shows that 72.2% of male children had levels below this limit. Thus, for these children, the limit was replaced with an imputed value of 0.16/sqrt(2) = 0.113. As I described, this simply shifted the original lower limit. The decision to do this means that the standard errors have been deflated, causing spurious reductions in the p-value. The authors need to consider more sophisticated techniques, possible through regression methods, that can resolve this. (In this setting, the data are termed “left truncated”.)

Response: We thank the reviewer for this valuable comment. We agree that replacing the limit with a single number does not solve the problem of measuring limitation. In the meantime, we understand that truncated regression is commonly used when sample has been truncated. However, the truncated variable should be dependent variable. In our study, the dependent variable is the serum total testosterone that was not truncated. The truncated variables here are blood metal concentrations. Replacing the limit with a single number does not help for detection limit, but here we did not use the observed values. Instead, we used the categories described in the ‘Statistical Analysis’ section, e.g. using quartiles when more than 75% of the samples were above the limit. In this case, it does not matter whether we replaced the unobserved values with a single number because it does not change the rank/order of those subjects. Thus it does not affect the categories and the results will not change. We appreciate the reviewer’s thoughtful comment, but since this is beyond the scope of this paper, we did not include truncated regression in the manuscript.

Response to comment: The authors have performed multiple testing on the same data and their results need to be considered quite carefully because it might be a chance finding. Let me demonstrate. The authors tested five metals (Cd, Pb, Hg, Mn, Se) on four groups (male children, female children, male adolescents, female adolescents) under three models (model 1 and model 2 and test for trend). Thus, the number of independent analyses conducted on the data is 5 x 4 x 3 = 60. That they have found about eight statistically significant results is hardly surprising, especially when they were not expecting these results in the first place. I strongly recommend that the authors adjust the familywise error rate.

Response: We thank the reviewer for pointing this out. We agree multiple testing should be considered here. Model 2 was used to verify the findings in model 1, thus we did not consider this in multiple testing. Also, the five metals were fairly independent; we did not consider it in multiple testing either. However, we did perform multiple testing for the four subgroups (male children, female children, male adolescents, female adolescents). The p-values were adjusted for multiple testing using least significant difference (LSD) method. Detailed modification can be found in the ‘Statistical Analysis’ section. All p-valued were updated with adjusted p-values.

Response to comment: Finally, to my mind, the more important issue here is not the degree to which heavy metals affect the level of testosterone, but whether these levels are associated with levels that are in the range for clinical action. The important *clinical* question is whether heavy metal concentrations are related to clinical testosterone deficiency in children and adolescents.

Response: We are genuinely grateful and appreciative for the reviewer’s thorough comments and suggestion to improve the quality of the manuscript. The authors carefully addressed the three issues arisen by the reviewer. Changes and modifications were made accordingly. In this study, we are trying to detect the difference in level of testosterone between subjects with high and low metal exposures. This will provide some clinical guidance in polycystic ovary syndrome (PCOS), cancer, altered pubertal development, hormone imbalances et al. An estimated 5 to 7 million women in the United States (U.S) suffer with the effects of PCOS; and PCOS can occur in girls as young as 11 years old. PCOS is the most common hormonal disorder among women of reproductive age and is the leading cause of infertility. Altered pubertal development may be at greater risk for psychological disorders and alcohol and substance abuse during adolescence. Although clinical testosterone deficiency in children and adolescents is an important problem, it is not our primary aim of this study. We are considering this in our next project. Again, we appreciate the reviewer’s comments, which were of great help to improve our work.

Reviewer #2:

Response to comment: General comments: Define all abbreviations the first time they are used. Abbreviations defined in the abstract should be redefined in the body of the manuscript.

Response: We are very sorry for our negligence. All abbreviations for the first time have been defined in the body of the manuscript.

Response to comment: The abbreviation for serum TT levels is not consistent throughout the manuscript.

Response: We are sorry for our negligence. We have corrected it.

Response to comment: There are many details are needed, For an example on the introduction and discussion include reference to many studies for which the model studied (human, rats, mice) is not identified and the route of exposure is not provided.

In the “Introduction and Discussion” section, there are repetition in many paragraphs. Please avoid redundancies.

In the “Discussion” section the authors need to explain the significance of their findings and the novelty of their study and should substantiate their findings with already available relevant scientific information.

Discussion is too long, hard to follow and could be better organized.

Response: We are genuinely grateful for the reviewer’s suggestion to improve the quality of the manuscript. We have reorganized the “Introduction and Discussion” section according to your comments. Please see the “Introduction and Discussion” section.

Response to comment: Parts of the Discussion section are particularly hard to understand. Professional assistance is recommended.

Response: According to your comment, this manuscript has been carefully re-checked by us and then it was sent to a professional English editing company for language correction.

Response to comment: In result caption section. Table 2. please add table legand blew the table

Response: We thank the reviewer for pointing this out. We have added table legand below the table 2. Please see Table2.

Reviewer #3:

Response to comment: The manuscript describes the data taken on metals levels in blood and their association with testosterone levels in children and adolescents. The authors have successfully correlated two metals concentrations (Cd and Mn) with testosterone concentrations in the subjects, highlighting the fact that environmental exposure to heavy metals may lead to altered testosterone levels in growing children. Overall the manuscript describes interesting findings, which are important to publish.

However, I have few questions in mind while reading this manuscript for review purpose, which the authors need to answer before the manuscript is accepted for publication.

Response: We are genuinely grateful and appreciative for the reviewer’s thorough comments to improve the quality of the manuscript. Most studies assessing the reproductive endocrine-disrupting effect of low, environmentally-relevant metal exposures in adults have focused on non-essential metals (cadmium and lead), whereas information on other potential endocrine-disrupting metals is still scant. Moreover, children and adolescents are at the ages where susceptibility to the adverse health effects of endocrine disruptors is most concerning. However, few studies have focused on the relationship between environmental metal exposure and endogenous androgen hormone levels in children and adolescents. Therefore, in this study, we are trying to detect the difference in level of testosterone between subjects with high and low environmental metals exposure (cadmium, lead, mercury, manganese, and selenium) in children and adolescents. This will provide some clinical guidance in polycystic ovary syndrome (PCOS), cancer, altered pubertal development, hormone imbalances et al. An estimated 5 to 7 million women in the United States (U.S) suffer with the effects of PCOS; and PCOS can occur in girls as young as 11 years old. PCOS is the most common hormonal disorder among women of reproductive age and is the leading cause of infertility. Altered pubertal development may be at greater risk for psychological disorders and alcohol and substance abuse during adolescence.

Reviewer #4:

Introduction:

Response to comment: More description of previous epidemiologic studies regarding the correlation of metals such as lead, mercury, manganese, selenium and levels of androgen hormones is necessary.

Response: We are genuinely grateful the reviewer’s suggestions to improve the quality of the manuscript. We have reorganized the “Introduction” section according to your suggestions. Please see paragraph 3 of the “Introduction” section in page 3-4.

Response to comment: It is also necessary to give clear description of total testosterone (TT). Were serum T or serum TT levels given in the cited epidemiological studies? In the manuscript, sometimes serum T is given while sometimes serum TT is given. Please make these term clear.

Response: We are very sorry for our negligence. We have made these terms clear (testosterone and serum total testosterone). We also have explained the differences between testosterone and serum total testosterone. Please see paragraph 2 of the “Discussion” section in page 11-12.

Response to comment: At page 3, 3rd paragraph, the cited animal studies of Cd and Hg are not related to androgen hormone levels, more relevant literature is needed.

Response: We are genuinely grateful and appreciative for the reviewer’s suggestions to improve the quality of the manuscript. We have reorganized the “Introduction” section according to your suggestions. Please see paragraph 3 of the “Introduction” section in page 3-4.

Material and Methods:

Response to comment: full name of NCHS, LOD should be given.

Response: We are very sorry for our negligence. Full name of NCHS, LOD have been given. Please see paragraph 1of page 5 and paragraph 2 of page 6.

Response to comment: Page 5, 2.2 Serum TT: information of blood sampling should be given, were the blood samples for serum TT collected at the same time point as blood samples of metals?

Response: We are sorry for our negligence. Information of blood sampling have been given, please see section 2.2 in page 5.The blood samples for serum TT was collected at the same time point as blood samples of metals.

Response to comment: Page 5, last two lines at the bottom: sentence “Serum TT was log-transformed… was skewed left.” should be in the Statistical Analysis section.

Response: We have accepted your suggestion, please see the “Statistical Analysis”section.

Response to comment: Page 6, 2.4 Covariates: what is the reason to choose these confounding variables? Is the selection of confounders based on literature or Directed Acyclic Graph (DAG) or other methods?

Response: We choosed the following as potential confounding variables: age, race/ethnicity, poverty income ratio (PIR), obesity, seasons of collection, times of venipuncture, and serum cotinine. Age and race/ethnicity are demographic factors. PIR is a socioeconomic factor. Obesity is associated with androgen imbalances in body（Escobar-Morreale HF, Santacruz E, Luque-Ramírez M, Botella Carretero JI. Prevalence of 'obesity-associated gonadal dysfunction' in severely obese men and women and its resolution after bariatric surgery: a systematic review and meta-analysis. Hum Reprod Update. 2017; 23(4):390-408.）. Levels of serum TT in body have a wide variation due to diurnal, weekly and seasonal variations. The diurnal variations lead to a peak in the serum T levels in the early morning followed by a progressive decline to the nadir in the evening. Nadir values are approximately 15% lower than the peak morning values (Paduch DA, Brannigan RE, Fuchs EF, Kim ED, Marmar JL, Sandlow JI. The laboratory diagnosis of testosterone deficiency. Urology. 2014; 83(5): 980-988.). Serum cotinine is a biomarker of exposure to environmental tobacco smoke. The selection of these confounders was based on literatures (such as 1. Meeker JD, Rossano MG, Protas B, Padmanahban V, Diamond MP, Puscheck E, Daly D, Paneth N, Wirth JJ. Environmental exposure to metals and male reproductive hormones: circulating testosterone is inversely associated with blood molybdenum. Fertil Steril. 2010; 93(1): 130-140. 2. Menke A, Guallar E, Shiels MS, Rohrmann S, Basaria S, Rifai N, Nelson WG, Platz EA. The association of urinary cadmium with sex steroid hormone concentrations in a general population sample of us adult men. BMC Public Health 2008; 8, 72. 3. Scinicariello F, Buser MC. Serum Testosterone Concentrations and Urinary Bisphenol A, Benzophenone-3, Triclosan, and Paraben Levels in Male and Female Children and Adolescents: NHANES 2011-2012. Environ Health Perspect. 2016; 124(12):1898-1904.).

Response to comment: Page 7, line 1-2: Please give the explanation for “we combined underweight and normal weight in one category”. What is the background to do so?

Response: We thank the reviewer for the comment. There are two reasons that we combined underweight and normal weight in one category. First, obesity is associated with associated with androgen imbalances in body. （Escobar-Morreale HF, Santacruz E, Luque-Ramírez M, Botella Carretero JI. Prevalence of 'obesity-associated gonadal dysfunction' in severely obese men and women and its resolution after bariatric surgery: a systematic review and meta-analysis. Hum Reprod Update. 2017; 23(4):390-408.）Second, we combined underweight and normal weight in one category, which are based on literatures (1. Scinicariello F, Buser MC. Serum Testosterone Concentrations and Urinary Bisphenol A, Benzophenone-3, Triclosan, and Paraben Levels in Male and Female Children and Adolescents: NHANES 2011-2012. Environ Health Perspect. 2016; 124(12):1898-1904. 2. Kresovich, J. K., Argos, M. & Turyk, M. E. Associations of lead and cadmium with sex hormones in adult males. Environ. Res. 2015; 142: 25–33. ).

Response to comment: Page 7, line 7: please give a short description of serum cotinine measurement. Sentence “ serum cotinine was log-transformed” should be in the Statistical Analysis section.

Response: We have accepted your suggestion, please see the “Statistical Analysis”section.

Statistical Analysis:

Response to comment: Page 7, The statistical power of category variables is generally weaker than continuous variables. For the association analysis of blood levels of metals and serum TT concentrations, authors only performed the linear regression analysis using quartiles and tertiles of metals while not run analysis for continuous metal data. Please clarify it.

Response: We thank the reviewer for this valuable comment. Using quartiles and tertiles for continuous variable will lose some power. However, there are two reasons that we use quartiles and tertiles, not the continuous values. First, there are significant amount of blood levels of metals were unobservable due to the lower detection limit (LOD). A commonly used method is to replace all unobservable values below LOD by a single value, e.g. LOD/2 or LOD/√2. But this does not solve the problem, it just shifts the limits. If we use quartiles and tertiles, the results will not be affected. It does not matter whether we replaced the unobserved values with a single number because it does not change the rank/order of those subjects. Thus it does not affect the categories and the results will not change. Second, we are based on literatures, (1. Scinicariello F, Buser MC. Serum Testosterone Concentrations and Urinary Bisphenol A, Benzophenone-3, Triclosan, and Paraben Levels in Male and Female Children and Adolescents: NHANES 2011-2012. Environ Health Perspect. 2016; 124(12):1898-1904. 2. Kresovich, J. K., Argos, M. & Turyk, M. E. Associations of lead and cadmium with sex hormones in adult males. Environ. Res. 2015;142: 25–33. ) which used quantiles and tetrtiles most of the time.

Response to comment: In the Table 3-7, Model 1 and Model 2 are given. However, the description of Model 1 and Model 2 is not given here. Please clarify why use these two models and give the corresponding description in Statistical analysis section.

Response: We thank the reviewer for the comment. We have descripted in “Statistical analysis” section, please see page 8 line6-8, Model 1 controlled for age, race and BMI. Model 2 controlled for PIR, seasons of collection, times of venipuncture, and serum cotinine, in addition to the covariates of model 1. Model Model 1 is only to adjust demographic factors. In addition to adjusting the demographic factors, model 2 also adjusted for confounding factors that may affect serum TT levels in our sample. These confounding factors were based on literatures. (such as Scinicariello F, Buser MC. Serum Testosterone Concentrations and Urinary Bisphenol A, Benzophenone-3, Triclosan, and Paraben Levels in Male and Female Children and Adolescents: NHANES 2011-2012. Environ Health Perspect. 2016; 124(12):1898-1904. Meeker JD, Rossano MG, Protas B, Padmanahban V, Diamond MP, Puscheck E, Daly D, Paneth N, Wirth JJ. Environmental exposure to metals and male reproductive hormones: circulating testosterone is inversely associated with blood molybdenum. Fertil Steril. 2010; 93(1): 130-140.)

Results

Response to comment:Page 8, line 3 from bottom: sentence “A large portion (98.6%-84.0%) of the samples had blood lead and total mercury levels > LOD” is not clear. This sentence should be reformulated to separately describe lead and mercury.

Response: We have accepted your suggestion, please see paragraph 2 of the “Result”section in page 8-9.

Response to comment:Page 8, last line: sentence “The median concentrations of all blood metals were higher in adolescents than in children. Are the differences statistically significant?

Response: We are very sorry for our negligence. We have corrected it.

Response to comment:Page 10, line 6-8: sentence “ The mean serum TT was significantly lower for all quartiles of blood selenium than that of the lowest quartile in all population subgroups.” is not precise. This is the case only for female children. Please check!

Page 10, line 1-2 of last paragraph: sentence “ As seen in Table 7…. in all population subgroups” is not precise. This is the case only for female adolescents. Check!

Response: We thank the reviewer for the comment. According to reviewer#1 suggestions, we employed weighted multivariable linear regression models using NHANES sampling weights to evaluate the association between log-transformed serum TT. p-values were adjusted for multiple testing using least significant difference (LSD) method. Details of the approach were described in the ‘Statistical Analysis’ section. The tables, results and conclusions were updated accordingly.

Discussion:

Response to comment: beware of “serum T” and “serum TT”. Are they same term?

Response: We are very sorry for our negligence. We have corrected it.

16. Response to comment: Page11, line 2-6 of 2nd paragraph: sentences “ In a previous study, Meeker et al…. which is in contrast to the results of the present study.” is not clear. Did Meeker measure serum TT or serum T? What is the difference between serum T and serum TT in these sentences? Serum T is free testosterone?

Response: We are genuinely grateful for the reviewer’s suggestion to improve the quality of the manuscript. We have reorganized the “Discussion” section according to your comments. Please see the “Discussion” section.

Response to comment: Page 15, line 2-3: sentence “ Our findings… may not be generalizable to environmental .. “ is not clear. Reformulation is necessary.

Response: We are genuinely grateful for the reviewer’s comments to improve the quality of the manuscript. We have reformulated the sentence. Please see page 15, line 2-4.

Response to comment: Table 3-7: sample numbers of each quartile or tertile should be given in the tables.

Response: We have shown sample numbers of each quartile or tertile in table3-7. Please see table 3-7.

Reviewer #5:

Response to comment: The manuscript entitled "Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011-2012"aimed to investigate whether there is an association between exposure to heavy metals and testosterone levels in children and adolescents. The work was well conducted, presents a relevant sample population and the results were explored through a consistent statistical analysis. The results indicated that some blood metals were positively associated with serum TT levels in female and male adolescents. However, the introduction of the article does not value the importance of the study. Much of the introduction (page 4, line 3-17) contains elements that are also cited in the discussion. Alternatively, the authors should explore in the introduction what are the sources or means of exposure of each of the heavy metals studied, as well as problematize how this exposure can impact the health of this specific population. Thus, I suggest that the authors make a comprehensive review of the introduction of the manuscript. In addition, a general review of writing is recommended, as several spelling errors were found throughout the text.

Response: We are genuinely grateful and appreciative for the reviewer’s thorough comments to improve the quality of the manuscript. We have reorganized the “Introduction and Discussion” section according to your comments. This manuscript has been carefully re-checked by us and then it was sent to a professional English editing company for language correction.

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PLoS One. doi: 10.1371/journal.pone.0224892.r003

Decision Letter 1

Yi Hu

11 Oct 2019

PONE-D-19-17206R1

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

PLOS ONE

Dear Dr. Hu,

We would appreciate receiving your revised manuscript by Nov 25 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Yi Hu

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PLOS ONE

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Reviewer #2: Yes

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Reviewer #2: Yes

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Reviewer #5: Yes

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Reviewer #1: (No Response)

Reviewer #2: After reviewing the manuscript that entitled (Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012) and make the first review and give some kind of modification . i find the following I accept all the modification and recommend to accept the manuscript

Reviewer #3: The revised version is in acceptable form now. can be proceeded further for publication in the PlosOne Journal

Reviewer #4: The author took into account of the raised questions and made the corresponding revision based on the comments. The revised manuscript is improved significantly.

A list of abbreviations can be given.

Page 6, section 2.5. Add” The selection of these confounders was based on literatures” in front of “ Race/ethnicity was… “

Reviewer #5: (No Response)

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PLoS One. 2019 Nov 7;14(11):e0224892. doi: 10.1371/journal.pone.0224892.r004

Author response to Decision Letter 1

22 Oct 2019

Dear editor:

Thank you very much for your letter and further instructions. We have carefully studied the comments and made corrections which we hope would meet with approval. Revisions are marked in red in the paper. The main corrections in the paper and responses to the reviewer’s comments are listed below.

Sincerely yours,

Rongkui Hu, M.M.

E-mail: xiangyu198110@163.com

Responses to the reviewers

We sincerely thank all the reviewers for their positive and constructive comments and suggestions.

Reviewer #4:

1. Response to comment: Page 6, section 2.5. Add” The selection of these confounders was based on literatures” in front of “ Race/ethnicity was… ”

Response: We have accepted your good suggestion, Please see Page 6，section 2.5.

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PLoS One. doi: 10.1371/journal.pone.0224892.r005

Decision Letter 2

Yi Hu

24 Oct 2019

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

PONE-D-19-17206R2

Dear Dr. Hu,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

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Academic Editor

PLOS ONE

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Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0224892.r006

Acceptance letter

Yi Hu

29 Oct 2019

PONE-D-19-17206R2

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

Dear Dr. Hu:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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With kind regards,

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on behalf of

Prof. Yi Hu

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

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Data Availability Statement

All relevant data are within its Supporting Information files.

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PERMALINK

Blood metal levels and serum testosterone concentrations in male and female children and adolescents: NHANES 2011–2012

Qi Yao

Ge Zhou

Meilin Xu

Jianguo Dai

Ziwei Qian

Zijing Cai

Luyao Zhang

Yong Tan

Rongkui Hu

Roles

Abstract

Introduction

Materials and methods

Study population

2.2 Blood sample

2.3 Serum total testosterone levels

2.4 Blood metals

2.5 Covariates

2.6. Statistical analysis

Results

Table 1. Characteristics of the 6–19-year-old children and adolescent participants in NHANES 2011–2012.

Table 2. The distribution of metal concentrations in the blood of the 6–19-year-old children and adolescent participants in NHANES 2011–2012.

Table 3. Percent differences (95% CI) in the serum TT by quartiles of blood lead exposure, NHANES, 2011–2012using weighted regression models.

Table 4. Percent differences (95% CI) in serum TT betweenthree blood cadmium exposure levels, NHANES, 2011–2012using weighted regression models.

Table 5. Percent differences (95% CI) in serum TT by quartiles of blood mercury exposure, NHANES, 2011–2012using weighted regression models.

Table 6. Percent differences (95% CI) in serum TT by quartiles of blood selenium exposure, NHANES, 2011–2012using weighted regression models.

Table 7. Percent differences (95% CI) in serum TT by quartiles of blood manganese exposure, NHANES, 2011–2012using weighted regression models.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

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Yi Hu

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Author response to Decision Letter 0

Decision Letter 1

Yi Hu

Roles

Author response to Decision Letter 1

Decision Letter 2

Yi Hu

Roles

Acceptance letter

Yi Hu

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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