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. 2011 Jul 21;26(10):2887–2895. doi: 10.1093/humrep/der250

The association between cadmium, lead and mercury blood levels and reproductive hormones among healthy, premenopausal women

LW Jackson 1,*, PP Howards 2, J Wactawski-Wende 3, EF Schisterman 4
PMCID: PMC3174033  PMID: 21778284

Abstract

BACKGROUND

Cadmium, lead and mercury have been identified in human follicular fluid and ovarian tissue, and have been associated with adverse reproductive outcomes in epidemiologic studies; however, few studies have examined the relationship between blood metal levels and reproductive hormones.

METHODS

Among 252 premenopausal women aged 18–44 years, we examined the association between blood metal levels (cadmium, lead and mercury), cycle length, and reproductive hormones [FSH, LH, estradiol (E2) and progesterone] measured at clinically relevant time points in the menstrual cycle. The association between metal levels (continuous) and hormone levels was assessed using linear regression with hormone levels (natural) log transformed and the results interpreted as the percentage difference in hormone level per unit increase in metal level.

RESULTS

Median (interquartile range) cadmium, lead and mercury levels were 0.30 µg/l (0.19, 0.43), 0.87 µg/dl (0.68, 1.20) and 1.10 µg/l (0.58, 2.10), respectively. Each 1 µg/l increase in cadmium levels was associated with a 21% [95% confidence interval (CI): −2.9, 49.9] increase in early follicular phase E2 levels after adjusting for age, race/ethnicity, lead and mercury. This association decreased when restricted to never smokers (10%; 95% CI: −19.5, 51.3). Cadmium was also associated with a non-significant 9% (95% CI: −0.2, 19.9), or 2.7 day, increase in cycle length among never smokers. No associations were observed between lead or mercury and the outcomes in adjusted analyses.

CONCLUSIONS

Further evaluation of the association between cadmium, E2 and cycle length is warranted, taking into consideration cigarette smoke and its multiple components.

Keywords: cadmium, lead, mercury, estradiol, menstrual cycle

Introduction

Cadmium, lead and mercury are ubiquitous in the environment following many years of industrial use, with most adults having measurable levels of these nonessential elements in their blood. Blood lead levels in premenopausal, non-pregnant women primarily represent current exposures to lead through contaminated food or water, home renovations, lead-glazed pottery, certain health care products and/or folk remedies [Agency for Toxic Substances and Disease Registry (ATSDR), 1990], as well as bone lead stores released during bone turnover (Jackson et al., 2010). Generally, adult exposures to lead are low, unless one is exposed occupationally. Cadmium exposure is primarily from cigarette smoke, both active and passive, as well as consumption of green leafy vegetables, liver and kidney meats and shellfish [Agency for Toxic Substances and Disease Registry (ATSDR), 1999]. Mercury exposure is primarily through fish and shellfish consumption (organic), and to a lesser extent air pollution (inorganic) (Mahaffey, 2005). All three metals bioaccumulate in the body with lead primarily accumulating in bone where it has a half-life of 12–27 years (Gerhardsson et al., 1993; Bergdahl et al., 1998). Cadmium and mercury accumulate in the kidney and liver with the half-life of cadmium in the kidney being ∼30 years, while the half-life of mercury is ∼1–3 months (Roels et al., 1991; Jonsson et al., 1999).

All three metals have been identified in human follicular fluid (Zenzes et al., 1995; Paksy et al., 2001; Al-Saleh et al., 2008) and ovarian tissue (Varga et al., 1993), and have been associated with adverse reproductive outcomes in epidemiologic studies. While the biological mechanisms by which these metals may exert adverse reproductive effects have not been fully elucidated, toxicologic studies have provided some insights. Both lead and cadmium have been associated with altered steroidogenesis, decreased gonadotrophin binding and serum gonadotrophin levels in rats (Wiebe et al., 1988; Piasek and Laskey, 1994; Paksy et al., 1997; Priya et al., 2004; Nampoothiri and Gupta, 2006), and lead is associated with altered follicular growth and maturation in mice (Junaid et al., 1997). Cadmium has been shown to activate estrogen (ERα) and androgen receptors and inhibit the binding of estradiol (E2) to ERα (Young et al., 1977; Garcia-Morales et al., 1994; Stoica et al., 2000; Johnson et al., 2003; Brama et al., 2007). Lead and mercury have also been shown to inhibit the binding of E2, but are thought to have anti-estrogenic effects (Young et al., 1977; Martin et al., 2003).

The epidemiologic literature supports the hypothesized anti-estrogenic effects of lead (Selevan et al., 2003; Wu et al., 2003; Denham et al., 2005; Popovic et al., 2005; Chang et al., 2006) and the estrogenic effects of cadmium (Gerhard et al., 1998; Jackson et al., 2008), while the effects of mercury are less clear. Few studies have directly examined blood metal levels in relation to hormone levels and cycle length. While Krieg examined the association between blood lead levels, FSH and LH among premenopausal women, blood collection was not timed to particular stages of the menstrual cycle and was limited to women aged 35–60 years of age (Krieg, 2007). Studies examining blood metal levels and cycle length have been primarily cross-sectional or retrospective in design and therefore limited by self-reported recall of cycle length by women (De Rosis et al., 1985; Sikorski et al., 1987; Wang and Tian, 2004). Within the BioCycle study, 2005–2007 (see below), we examined the association between blood metal levels (cadmium, lead and mercury) and menstrual cycle function assessed by prospectively collected data on cycle length and serum hormone levels (FSH, LH, E2 and progesterone) as measured on clinically relevant days of the menstrual cycle.

Materials and Methods

Study population

This research was carried out as an ancillary study to the BioCycle Study, which has been described in detail elsewhere (Wactawski-Wende et al., 2009). Briefly, the BioCycle Study was designed to examine the association between endogenous hormones and biomarkers of oxidative stress across the menstrual cycle. The study was carried out at the University at Buffalo under an Intramural Research Program contract from the ‘Eunice Kennedy Shriver’ National Institute of Child Health and Human Development, from 2005 to 2007.

A total of 259 healthy women were recruited from the community and enrolled for up to two menstrual cycles. Premenopausal women aged 18–44 years were eligible for the study if they had a self-reported cycle length between 21 and 35 days. Women who reported the following were not eligible: BMI < 18 or >35 kg/m2; use of Depo-Provera, Norplant or an intrauterine device in the past 12 months; oral contraceptive or other hormonal supplements in the past 3 months; planning to attempt pregnancy in next the 3 months; actively trying to conceive in the past 6 months; currently pregnant or pregnant in the past 6 months; and breastfeeding in the past 6 months. In addition, women were excluded if they self-reported various medical conditions, medication or supplement use, or diets that may alter hormone or oxidative stress levels (Wactawski-Wende et al., 2009).

Eligible women who consented to participate in the BioCycle Study were asked to come to the study clinic eight times per cycle. The visit days were planned to capture critical windows of hormonal variability during the menstrual cycle and were approximately timed to early- and mid-follicular phase; E2 peak; LH surge; ovulation; and early-, mid- and late-luteal phase. (For the present study, data for three time points are analyzed.) Participants were provided with and trained to use the Clearblue Easy Fertility Monitor (Inverness Medical Innovations, Inc., Waltham, MA, USA) to help identify and time visits around the LH peak and ovulation (Howards et al., 2009).

During the screening and baseline visits, information on lifestyle factors and reproductive history was collected through structured questionnaires. Dietary information was obtained using a food frequency questionnaire developed by the Nutrition Assessment Shared Resource of Fred Hutchinson Cancer Research Center (http://www.fhcrc.org/science/shared_resources/nutrition/ffq). Height and weight were measured at the baseline visit for the determination of BMI.

Exposure measurement

Whole blood was collected during the screening visit for the measurement of cadmium, lead and mercury with the median time between the screening visit blood draw and first day of the study cycle being 16 days [interquartile range (IQR): 11–31 days]. Concentrations in whole blood primarily represent recent exposure, which is hypothesized to have acute effects resulting in altered follicular growth and steroidogenesis in the subsequent cycle. Collection kits and EDTA purple top tubes were prescreened for trace metals by the Centers for Disease Control and Prevention (CDC). Samples were refrigerated until shipment to the CDC (Division of Laboratory Sciences, National Center for Environmental Health) where they were analyzed by inductively coupled plasma-mass spectrometry (ICP-MS). Limits of detections (LOD) using this method were 0.2 µg/dl for lead (0% <LOD), 0.2 µg/l for mercury (13% <LOD) and 0.3 µg/l for cadmium (27% <LOD). Values below the LOD were used as obtained by ICP-MS, without substitution in order to minimize potential measurement error (Richardson and Ciampi, 2003; Schisterman et al., 2006; Whitcomb and Schisterman, 2008).

Outcome assessment

During each cycle visit, women provided 12-h fasting blood specimens. Samples were processed according to a standardized protocol and stored at −80°C. FSH, LH and progesterone concentrations were measured by Specialty Laboratories Inc. (Valencia, CA, USA) using a solid-phase competitive chemiluminescent enzymatic immunoassay on a DPC IMMULITE 2000 analyzer (Siemens Medical Solutions Diagnostics, Deerfield, IL, USA). E2 concentrations were determined by radioimmunoassay (Kaleida Health Center for Laboratory Medicine, Buffalo, NY, USA).

Only hormone levels from the first study cycle were used for this analysis. This was based upon the hypothesized acute effect of metals as described above, and the potential fluctuation of cadmium and mercury levels over time caused by sporadic exposures to cigarette smoke and fish consumption. All cycles were standardized to a 28-day cycle as described by Whitcomb et al. (2010). FSH and E2 levels quantified during the early follicular phase (standardized Day 2) were used as measures of ovarian reserve, and follicular growth and maturation. LH levels during the ovulatory window (standardized Day 13), and progesterone levels during the mid-luteal phase (standardized Day 22) were examined as measures of ovulation and corpus luteum function. Menstrual cycle length was determined using prospectively collected data and defined as the difference in time between the date menstrual bleeding began in the first cycle and the date menstrual bleeding began in the next cycle.

Statistical analysis

The exposure and outcome variables were not normally distributed with further analyses taking this into consideration as indicated. Median blood metal levels, hormone levels and cycle length were examined across categories of potential confounders and compared using the Kruskal–Wallis test, and the correlation between metals was examined using Pearson's correlation coefficient. We examined the association between metal levels (continuous) and hormone levels using linear regression with hormone levels (natural) log transformed. Results were back transformed and interpreted as the percentage difference in hormone level per unit increase in metal level. Cycle length was investigated as both a continuous and dichotomous outcome variable in linear (log transformed) and logistic regression models, respectively. Logistic models compared women with short cycles (<25 days) or long cycles (>35 days) to women with normal cycles (25–35 days), independently. Factors shown in the literature to be associated with the metals or the outcomes of interest, or that changed the association between metals and outcomes by more than 10%, were examined as potential confounders including age, race/ethnicity, education, marital status, income, BMI, alcohol consumption, age at menarche, gravidity and parity; all variables were entered as categorized in Table I. Only age and race/ethnicity were found to be confounders and therefore retained in the final models. Models were not adjusted for smoking status given the small number of current and former smokers; however, in sub-analyses, we restricted all models to never smokers to eliminate potential confounding or effect modification by smoking status. Models were run for each metal independently, then including all metals in the model together. Statistical significance was set at P< 0.05. All analyses were completed in SAS Version 9.2 software (Cary, NC, USA).

Table I.

Median (IQR) blood metal levels stratified by demographic, lifestyle and reproductive factors, BioCycle Study, 2005–2007.

  n % Cadmium (µg/l)a
 Lead (µg/dl)b
 Mercury (µg/l)c
Median Percentile
 Median Percentile
 Median Percentile
25th 75th 25th 75th 25th 75th
Total Population 252 100 0.30 0.19 0.43 0.87 0.68 1.20 1.10 0.58 2.10
Age
 18–24 years 129 51 0.28 0.17 0.36 0.82 0.66 1.10 1.10 0.45 2.20
 25–29 40 16 0.32 0.18 0.47 0.90 0.67 1.40 1.25 0.74 2.60
 30–34 19 8 0.34 0.22 0.48 0.84 0.56 1.20 1.30 0.58 1.50
 35–39 32 13 0.29 0.20 0.36 0.93 0.67 1.25 1.15 0.77 1.80
 40+ 32 13 0.42 0.22 0.56 0.99 0.82 1.40 1.05 0.71 1.90
Race/ethnicity
 Non-Hispanic white 148 59 0.27 0.16 0.37 0.81 0.62 1.05 1.00 0.47 1.80
 Non-Hispanic black 48 19 0.31 0.20 0.47 0.86 0.69 1.10 1.05 0.63 1.55
 Other 56 22 0.36 0.27 0.53 1.15 0.81 1.60 1.65 0.80 2.75
Education
 High school degree or less 31 12 0.32 0.17 0.46 0.81 0.61 1.00 1.00 0.57 1.50
 Some college or associates degree 119 47 0.28 0.17 0.38 0.81 0.65 1.10 1.00 0.44 2.30
 College degree or higher 102 40 0.31 0.21 0.47 0.96 0.70 1.40 1.40 0.77 2.10
Marital status
 Married or living as married 64 25 0.31 0.20 0.45 0.89 0.69 1.20 1.00 0.75 1.75
 Neither married nor living as married 188 75 0.29 0.19 0.41 0.87 0.67 1.20 1.20 0.50 2.20
Income (n= 250)
 <$19 999 53 21 0.32 0.25 0.47 0.98 0.73 1.20 1.10 0.61 2.20
 $20 000–$39 999 60 24 0.32 0.21 0.49 0.97 0.69 1.35 1.35 0.81 2.30
 $40 000–$74 999 69 28 0.30 0.18 0.40 0.82 0.67 1.10 0.99 0.58 1.80
 $75 000 or more 68 27 0.28 0.15 0.38 0.81 0.65 1.05 1.15 0.44 2.35
BMI
  <18.5 kg/m2 9 4 0.35 0.28 0.48 0.93 0.81 1.10 1.40 0.88 1.50
 18.5–24.9 152 60 0.30 0.19 0.41 0.92 0.69 1.20 1.30 0.61 2.25
 25.0–29.9 65 26 0.28 0.18 0.39 0.75 0.61 1.00 0.97 0.54 1.80
 >29.9 26 10 0.32 0.22 0.44 0.80 0.72 1.40 0.97 0.45 1.70
Current smoking status (n= 249)
 Never 201 81 0.29 0.19 0.39 0.84 0.67 1.10 1.10 0.58 2.20
 Former 37 15 0.31 0.19 0.45 0.97 0.81 1.30 1.00 0.63 1.80
 Current 11 4 0.84 0.35 1.00 1.20 0.76 1.50 1.40 1.00 1.80
Alcohol (n= 250)
 Never 82 33 0.31 0.20 0.43 0.77 0.66 1.10 0.99 0.57 1.80
 <1 drink per week 105 42 0.31 0.19 0.42 0.85 0.65 1.20 1.10 0.44 1.80
 1 or more drinks per week 63 25 0.27 0.17 0.44 1.00 0.81 1.30 1.50 0.91 2.40
Gravidity (n= 246)
 No prior pregnancies 170 69 0.29 0.19 0.41 0.86 0.67 1.20 1.10 0.52 2.20
 Any prior pregnancies 76 31 0.32 0.21 0.45 0.90 0.69 1.20 1.15 0.80 1.75
Parity (n= 246)
 Nulliparous 181 74 0.29 0.19 0.41 0.89 0.68 1.20 1.20 0.57 2.20
 Parous 65 26 0.31 0.21 0.45 0.85 0.68 1.10 1.10 0.66 1.60
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IQR, interquartile range.

aCadmium concentrations differed significantly across categories of age, race/ethnicity and smoking.

bLead concentrations differed significantly across categories of age, race/ethnicity, education, income, smoking and alcohol consumption.

cMercury concentrations differed significantly across categories of race/ethnicity, education and alcohol consumption.

Results

Metals were quantified for 252 of the 259 women who participated in the study. Among these women, 249 had FSH and E2 measured during the early follicular phase, 213 had peak LH levels measured during the ovulatory window, 217 had progesterone levels measured during the mid-luteal phase and 247 had data on cycle length for the first study cycle. Overall, the study population was young with 51% of the women between the ages of 18 and 24 years (Table I). The majority of the women identified themselves as being white, non-Hispanic (59%) and 40% had a college degree or higher. Only 25% of the population reported drinking alcohol at least once a week, and 81% reported never smoking. Sixty-nine percent of women reported never being pregnant; among the 76 women reporting a previous pregnancy, 65 women reported a previous live birth. Overall, 36% of the study population was overweight or obese.

Median (IQR) cadmium, lead and mercury levels were 0.30 µg/l (0.19, 0.43), 0.87 µg/dl (0.68, 1.20) and 1.10 µg/l (0.58, 2.10), respectively (Table I). Blood lead and cadmium levels increased significantly with age (lead: P= 0.03; cadmium: P= 0.02); mercury levels did not differ significantly but were highest in the 30–34 year age group. Median metal levels differed significantly by race/ethnicity with those in the ‘other’ group having the highest concentrations for all three metals (lead and cadmium: P< 0.01; mercury: P= 0.02). This was primarily explained by women of Asian descent (n= 36) who had higher blood metal levels when compared with all non-Asian women (n= 216; P< 0.01). Blood lead levels decreased with increasing income (P= 0.04), but increased with smoking (P= 0.03) and alcohol consumption (P= 0.01). Blood cadmium levels differed by smoking status (P< 0.01) with current smokers having the highest cadmium levels, followed by former smokers, and never smokers. Non-smokers (never and former) who reported environmental tobacco smoke (ETS) exposure at baseline had similar blood cadmium levels (n= 118; median: 0.28 µg/l; IQR: 0.19, 0.39) when compared with non-smokers who reported no ETS exposure (n= 97; median: 0.32 µg/l; IQR: 0.19, 0.45). Mercury levels differed by alcohol consumption with those consuming one or more drinks per week having the highest levels when compared with those drinking less than one drink per week and never drinkers (P= 0.02). Mercury levels increased with increasing frequency of fish and shellfish consumption (P< 0.01): never (median: 0.38 µg/l; IQR: 0.16, 0.93), one to four times per month (median: 1.00 µg/l; IQR: 0.53, 1.60) and greater than four times per month (median µg/l: 1.60; IQR: 1.00, 2.65). Blood lead levels were weakly but significantly correlated with cadmium (r = 0.15; P= 0.02) and mercury levels (r = 0.14; P= 0.03), and cadmium and mercury levels were similarly correlated (r = 0.15; P= 0.02).

Follicle-stimulating hormone

The median serum FSH level as measured during the early follicular phase was 6.3 mIU/ml (IQR: 5.3, 7.8; Table II). FSH levels increased with age, gravidity and parity, and decreased with increasing BMI. In unadjusted analyses, neither lead nor mercury was associated with FSH levels (Table III). A 1 µg/l (SD: 0.3) increase in cadmium was associated with a 20% [95% confidence interval (CI): −2.9, 46.9] increase in FSH levels; however, after adjusting for age and race/ethnicity, the association was attenuated and not statistically significant.

Table II.

Median (IQR) serum hormone levels and cycle length, BioCycle Study, 2005–2007.

  Cycle stage n Median Percentile
25th 75th
FSH (mIU/ml) Early follicular phase 249 6.3 5.3 7.8
Estradiol (pg/ml) Early follicular phase 249 32.0 25.0 43.0
LH (ng/ml) Ovulatory window 213 31.6 18.9 42.8
Progesterone (ng/ml) Mid-luteal phase 217 10.1 7.0 12.4
Cycle length (days) 247 28 26 31
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IQR, interquartile range.

Table III.

Unadjusted and adjusted results for the percentage difference in serum hormone levels or cycle length per unit change in blood metal levels, BioCycle Study, 2005–2007.

  Unadjusted
 Model 1a
 Model 2b
% difference 95% CI % difference 95% CI % difference 95% CI
FSH (mIU/ml; n= 249)
 Cadmium (µg/l) 19.5 −2.9, 46.9 3.5 −15.4, 26.5 3.4 −15.7, 26.7
 Lead (µg/dl) 3.9 −5.5, 14.1 −2.3 −10.9, 7.2 −2.5 −11.2, 7.0
 Mercury (µg/l) 2.2 −2.3, 6.9 1.1 −3.2, 5.6 1.1 −3.3, 5.7
Estradiol (pg/ml; n= 249)
 Cadmium (µg/l) 24.3 1.1, 52.9 21.3 −2.1, 50.3 20.6 −2.9, 49.9
 Lead (µg/dl) 5.8 −3.7, 16.3 5.6 −4.4, 16.7 4.9 −5.0, 15.9
 Mercury (µg/l) −0.1 −4.5, 4.6 0.0 −4.6, 4.8 −0.6 −5.2, 4.2
LH (ng/ml; n= 213)
 Cadmium (µg/l) 1.8 −26.3, 40.5 −7.7 −33.9, 28.9 −7.1 −33.6, 30.0
 Lead (µg/dl) 6.3 −8.5, 23.5 1.6 −13.0, 18.6 2.5 −12.3, 19.9
 Mercury (µg/l) −1.8 −8.9, 6.0 −3.4 −10.5, 4.4 −3.4 −10.6, 4.4
Progesterone (ng/ml; n= 217)
 Cadmium (µg/l) 3.9 −27.8, 49.5 −4.8 −34.4, 38.4 −7.7 −36.9, 35.0
 Lead (µg/dl) 10.0 −6.6, 29.5 4.7 −12.0, 24.5 4.6 −12.2, 24.6
 Mercury (µg/l) 5.3 −2.8, 14.1 3.4 −5.0, 12.5 3.5 −5.0, 12.7
Cycle Length (days) (n= 247)
 Cadmium (µg/l) 1.0 −5.4, 7.7 2.8 −3.6, 9.6 2.7 −3.8, 9.6
 Lead (µg/dl) 0.2 −2.8, 3.2 0.3 −2.7, 3.4 0.2 −2.8, 3.3
 Mercury (µg/l) 0.5 −0.9, 1.9 0.3 −1.2, 1.7 0.2 −1.2, 1.6
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CI, confidence interval.

aModels adjusted for age (18–24, 25–29, 30–34, 35–39, 40–44 years) and race/ethnicity (non-Hispanic white, non-Hispanic black, other) in linear regression.

bModels adjusted for cadmium, lead, mercury, age (18–24, 25–29, 30–34, 35–39, 40–44 years) and race/ethnicity (non-Hispanic white, non-Hispanic black, other) in linear regression.

Estradiol

The median serum E2 level as measured during the early follicular phase was 32.0 pg/ml (IQR: 25.0–43.0; Table II). Though E2 levels did not differ greatly by various demographic, lifestyle or reproductive factors, levels were highest among women who were 40 years of age or older, and among gravid and parous women. In unadjusted analyses, a 1 µg/l (SD: 0.3) increase in blood cadmium levels was associated with a 24% (95% CI: 1.1, 52.9) increase in E2 levels (Table III). After adjusting for lead, mercury, race/ethnicity and age, this association decreased marginally (21%; 95% CI: −2.9, 49.9) and was no longer statistically significant. When restricted to never smokers, the association between cadmium and E2 was weaker and imprecise in adjusted analyses (10%; 95% CI: −19.5, 51.3). Neither lead nor mercury was associated with serum E2 levels.

Luteinizing hormone

The median peak LH level as measured during the ovulatory window was 31.6 ng/ml (IQR: 18.9, 42.8). LH levels did not change greatly over categories of demographic, lifestyle or reproductive factors but was lowest among women who were 40 years of age or older. Women missing peak LH levels (n= 39) had slightly higher blood mercury levels (median: 1.5 µg/l; IQR: 0.7, 2.5) and lower FSH levels (median: 6.0 mIU/ml; IQR: 5.1, 7.3) when compared with women with peak LH levels (n= 213; median mercury: 1.0 µg/l; IQR: 0.6, 2.0 and median FSH: 6.3 mIU/ml; IQR: 5.3, 8.0). In both unadjusted and adjusted analyses, the associations between metals and peak LH levels were weak and imprecise.

Progesterone

The median serum progesterone level as measured during the mid-luteal phase was 10.1 ng/ml (IQR: 7.0, 12.4; Table II). Progesterone levels did not differ greatly by demographic, lifestyle or reproductive factors. Though not statistically significant, current smokers had lower progesterone levels (median: 7.6 ng/ml; IQR: 5.0, 12.0) when compared with former (median: 10.4 ng/ml; IQR: 7.1, 12.1) or never smokers (10.2 ng/ml; IQR: 7.2, 12.5). White, non-Hispanic women (median: 9.5 ng/ml; IQR: 6.8, 12.1) and Black, non-Hispanic women (median 9.9 ng/ml; IQR: 6.3, 13.1) had lower progesterone levels when compared with women of ‘other’ race/ethnicity (median: 11.5 ng/ml, IQR: 8.9, 13.0; P= 0.10). Overall, women with (n= 217) and without (n= 35) progesterone levels did not differ greatly; however, FSH levels were lower among women with missing progesterone levels (median: 4.5 mIU/ml; IQR: 3.2, 5.7) when compared with women with progesterone levels (median: 6.4 mIU/ml; IQR: 5.5, 8.1; P< 0.01). In unadjusted analyses (Table III), lead was associated with a 10% (95% CI: −6.6, 29.5) increase in progesterone levels; however, after adjusting for cadmium, mercury, age and race/ethnicity, this association diminished (5%; 95% CI: −12.2, 24.6). Cadmium and mercury were not associated with serum progesterone levels.

Cycle length

Median cycle length was 28 days (IQR: 26, 31; Table II) with length decreasing with increasing age, gravity and parity (P< 0.01). No association was observed between lead and mercury concentrations and cycle length in the full study population (Table III). In adjusted analyses, a 1 µg/l (SD: 0.3) increase in cadmium was associated with a 3% (95% CI: −3.8, 9.6) or 0.8 day increase in cycle length; however, when analysis was restricted to never smokers, the association strengthened and was associated with a 9% (95% CI: −0.2, 19.9) or 2.7 day increase in cycle length. In logistic regression, a 1 µg/l (SD: 0.3) increase in cadmium was moderately associated with having a cycle length >35 days (odds ratio: 4.2; 95% CI: 0.6, 28.3) when compared with a normal cycle length (25–35 days) after adjusting for age, race/ethnicity, lead and mercury (Table IV); however, this should be interpreted cautiously given the small number of women with cycle length >35 days (n= 17).

Table IV.

Unadjusted and adjusted odds ratios and 95% CIs for the association between blood metal levels and cycle length, BioCycle Study, 2005–2007.

  Unadjusted
 Adjusted
OR 95% CI OR 95% CI
Short versus normal cyclea,b
 Cadmium 1.7 0.4, 7.1 1.4 0.3, 7.0
 Lead 0.9 0.4, 2.0 0.9 0.4, 2.3
 Mercury 0.7 0.4, 1.1 0.7 0.4, 1.2
Long versus normal cyclea,b
 Cadmium 1.9 0.5, 6.9 4.2 0.6, 28.3
 Lead 0.6 0.2, 1.9 0.5 0.1, 1.9
 Mercury 1.2 0.9, 1.7 1.2 0.9, 1.7
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CI, confidence interval; OR, odds ratio.

aModels adjusted for cadmium, lead, mercury, age (18–24, 25–29, 30–34, 35–39, 40–44 years) and race/ethnicity (non-Hispanic white, non-Hispanic black, other) using logistic regression.

bShort cycle (<25 days; n= 22), normal cycle (25–35 days; n= 208) and long cycle (>35 days; n = 17).

Discussion

In this population of healthy, regularly menstruating women, we examined the association between blood metal levels and hormone levels as measured at clinically relevant time points during the menstrual cycle. Blood cadmium levels were positively associated with early follicular phase E2 levels; however, this effect diminished when limiting analyses to never smokers. Cadmium was also associated with a longer cycle length though not statistically significant. No associations were observed between lead or mercury and the outcomes of interest in adjusted analyses.

The major sources of cadmium in the general population are through cigarette smoke (both active and passive), shellfish, kidney and liver meats, and green leafy vegetables, with levels in food directly associated with contaminated water and soil [Agency for Toxic Substances and Disease Registry (ATSDR), 1999]. Median blood cadmium levels among current smokers in our study population (0.84 µg/l) were similar to those of women aged 20–44 years in the National Health and Nutrition Examination Survey (NHANES) 1999–2006 (0.84 µg); however, never smokers in our study had somewhat higher cadmium levels when compared with women in NHANES: 0.29 versus 0.21 µg/l, respectively (Mijal and Holzman, 2010). As indicated by the increasing blood cadmium levels with age, cadmium tends to bioaccumulate in the tissues of the kidney and liver, but has been found in uterine tissue (Nasiadek et al., 2005) and follicular fluid (Zenzes et al., 1995) with levels significantly higher in smokers than non-smokers (Varga et al., 1993; Zenzes et al., 1995).

While cigarette smoke has been associated with anti-estrogenic effects including a decreased risk of endometrial cancer and an earlier age at menopause (Baron et al., 1990; Parente et al., 2008; Zhou et al., 2008), cadmium, one of many contaminants in cigarettes, has been associated with estrogenic effects. Cadmium has been associated with an earlier onset of vaginal opening, increased uterine weights and enhanced mammary development in rats (Johnson et al., 2003); decreased gonadotrophin binding and altered steroidogenic enzyme activity in granulosa cells of rats (Priya et al., 2004; Nampoothiri and Gupta, 2006); menstrual cycle abnormalities among young women (Wang and Tian, 2004); endometriosis (Jackson et al., 2008); difficulties getting pregnant among married women (Wang and Tian, 2004); and preterm delivery (Laudanski et al., 1991; Fagher et al., 1993).

Based upon previous studies, it is unclear why cadmium would be associated with increased E2 levels during the early follicular phase; however, this association may be reflective of cigarette smoke exposure, and not cadmium. In epidemiologic studies, smoking has been associated with increased E2 levels (Windham et al., 2005), as well as shorter overall cycle length (Kato et al., 1999; Rowland et al., 2002), and shorter follicular phase length (Liu et al., 2004). Given the low prevalence of smoking in our study population, we were unable to examine effects among smokers; however, the observed association between cadmium and early follicular phase E2 in the main analysis decreased when restricted to never smokers. This is consistent with a study of men, in which smoking was shown to be a strong confounder (and not an effect modifier), explaining an observed association between cadmium and E2 levels in adjusted analyses (Menke et al., 2008). Alternatively, the lack of an association when excluding smokers may be due to exclusion of those individuals with the highest blood cadmium levels with there being a potential threshold effect. In regards to cycle length, the observed association between cadmium and increased cycle length became stronger when restricting analyses to never smokers, suggesting possible independent and opposing effects of cadmium and cigarette smoke on cycle length.

We did not observe any associations between blood lead or mercury levels and the outcomes of interest in adjusted analyses despite previous studies indicating they may have endocrine disrupting effects. This may be a reflection of the low lead and mercury levels experienced by our study population, or may indicate the lack of a true association with the measured hormones or cycle length. Alternatively, the study eligibility criteria, the timing of exposure measurement, and/or the selected biomarker of exposure (whole blood) may have limited our ability to detect an association as discussed below.

Our sample size (n= 252) may have limited our ability to detect significant effects between metals and the outcomes of interest, should an association exist. Furthermore, given the eligibility criteria and primary objectives of the BioCycle Study, the study population was comprised of healthy, young women, which may have decreased the variability in blood metal levels and outcome measures, thereby decreasing our power to detect associations. In addition, women with conditions potentially related to higher metal levels (e.g. shorter or longer menstrual cycle lengths, medication or supplement use, ever having treatment for infertility, presence of endometriosis or fibroids, history of polycystic ovary syndrome, kidney disease, diabetes, cancer, thyroid disease, endocrine dysfunction or treatment of anemia) were excluded, which may have limited our ability to detect a threshold effect if an association were present at higher metal levels but not lower metal levels. The exclusion of women with self-reported cycle lengths <21 days or >35 days limited our analysis of cycle length with only 22 women having an observed cycle length <25 days and 17 women having a cycle >35 days. Overall, the strict eligibility criteria for the study limit our ability to generalize the results to all premenopausal women.

We had good estimates of hormone levels as measured on clinically relevant days of the menstrual cycle, and then standardized to a 28-day cycle to ensure comparisons across women were being made at the same physiologic time point in the cycle. LH and progesterone levels were missing for 15% (n= 39) and 14% (n= 35) of women in the study, respectively; however, we did not find major differences between those with and without data that would explain the observed associations. As women with missing LH levels had slightly higher mercury levels, a possible inverse association between increasing mercury levels and decreased LH levels may have been missed. We had excellent measures of blood metal levels representative of current metal exposures. The majority of participants had metal levels measured within 16 days of the study cycle when follicles are growing and exposure may result in altered steroidogenesis and cycle length in the subsequent cycle. The study may have been limited if exposure was not measured during the critical window of exposure. Animal studies suggest that prenatal or childhood exposure may represent a sensitive window of exposure for lead and cadmium as the hypothalamic–pituitary–ovarian axis is developing during this time period (Wide, 1985; Wide and D'Argy, 1986; Wiebe et al., 1988; McGivern et al., 1991; Ronis et al., 1996, 1998; Dearth et al., 2002; Johnson et al., 2003). Alternatively, if cumulative metal exposure is more relevant to the outcomes of interest, metal levels should have been measured in alternative matrices, such as bone (lead), hair (mercury) or urine (cadmium).

This is one of the first studies to look at the association between metals and reproductive hormones in women. In adjusted analyses, we observed a non-significant increase in early follicular phase E2 levels in relation to cadmium; however, this association diminished after restricting analyses to never smokers. Cadmium was also potentially associated with an increased cycle length in never smokers. These observed associations between cadmium, E2 and cycle length need to be examined in future studies, taking into consideration cigarette smoke and its multiple components. The effects of lead and mercury on reproductive hormones deserve further study in larger and more representative populations.

Authors' roles

L.W.J.: conceived of the ancillary study, developed the associated study design, oversaw statistical analyses, interpreted results and wrote the manuscript. P.P.H.: helped to execute the parent study, completed statistical analyses and reviewed manuscript. J.W.-W.: carried out the parent study, and reviewed statistical analyses and manuscript. E.F.S.: conceived of and carried out the parent study, reviewed statistical analyses and manuscript.

Funding

This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health. None of the authors have competing financial interests related to this work.

Acknowledgements

We wish to thank the Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention for their technical assistance in analyzing samples for the quantification of blood metal levels.

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