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. Author manuscript; available in PMC: 2019 Feb 1.
Published in final edited form as: Environ Res. 2017 Oct 31;161:9–16. doi: 10.1016/j.envres.2017.10.047

Maternal and Paternal Serum Concentrations of Persistent Organic Pollutants and the Secondary Sex Ratio: A Population-based Preconception Cohort Study

Jisuk Bae a,*, Sungduk Kim b,c, Dana Boyd Barr d, Germaine M Buck Louis b
PMCID: PMC5747985  NIHMSID: NIHMS917256  PMID: 29096317

Abstract

Recent declines in the secondary sex ratio (SSR), defined as the ratio of males to females at birth, in some industrialized countries may be attributed to exposure to environmental toxicants such as persistent organic pollutants (POPs). This study aimed to evaluate the association of couples’ preconception exposure to POPs with the SSR. The study cohort comprised 235 couples who were enrolled in the Longitudinal Investigation of Fertility and the Environment (LIFE) Study between 2005 and 2009 prior to conception and prospectively followed through delivery of a singleton birth. Upon enrollment, couples’ serum concentrations (ng/g) were measured for 9 organochlorine pesticides, 1 polybrominated biphenyl, 10 polybrominated diphenyl ethers, and 36 polychlorinated biphenyls (PCBs). Birth outcome data including infant sex were collected upon delivery. Modified Poisson regression models were used to estimate the relative risks (RRs) and 95% confidence intervals (CIs) of a male birth for each chemical. Of the 56 POPs examined, maternal PCB 128 and paternal hexachlorobenzene were significantly associated with a female excess (RRs, 0.75 [95% CI, 0.60–0.94] and 0.81 [95% CI, 0.68–0.97] per 1 SD increase in log-transformed serum chemical concentrations, respectively), whereas maternal mirex and paternal PCB 128 and p,p′-dichlorodiphenyldichloroethylene were significantly associated with a male excess (RR range, 1.10–1.22 per 1 SD increase in log-transformed serum chemical concentrations). After adjusting for multiple comparisons, only maternal mirex remained significantly associated with the SSR. This exploratory study on multiple classes of POPs demonstrated no conclusive evidence on the association between parental preconception exposure to POPs and the SSR.

Keywords: endocrine disruptors, flame retardants, pesticides, polychlorinated biphenyls, sex ratio

1. Introduction

The secondary sex ratio (SSR) is the ratio of males to females at birth, while the primary sex ratio is the ratio at conception (Buck Louis and Platt 2011). Across multiple academic disciplines including demography, sociobiology, epidemiology, and environmental science, the SSR has long been the subject of scientific investigation, serving as a useful tool in monitoring population dynamics and health (McDonald et al. 2014). The stability and variability of the SSR observed at the population level have been proposed to be influenced by a variety of endogenous and exogenous factors, such as parental ages (Chahnazarian 1998; Jacobsen et al. 1999; Mathews and Hamilton 2005), birth order (Biggar et al. 1999; Mathews and Hamilton 2005), race/ethnicity (David et al. 2007; Mathews and Hamilton 2005), follicular phase length (Martin 1997; Weinberg et al. 1995), timing of conception within the menstrual cycle (Martin 1997; James 2008b), stress (Bae et al. 2017b; Fukuda et al. 1998; Zorn et al. 2002), endocrine and immunological effects (James 2008a; Ober 1992), and other environmental factors (Terrell et al. 2011). In particular, there has been speculation that recent declines in the SSR in some developed countries may be attributed to ubiquitous exposure to environmental toxicants (Davis et al. 2007; Grech et al. 2003; Mathews and Hamilton 2005). Indeed, the decreasing trends in the SSR are juxtaposed with other adverse trends in reproductive outcomes, such as testicular cancer, genitourinary malformations, fecundity impairments, and gynecologic disorders (Buck Louis et al. 2011a; Skakkebeak et al. 2001). Of late, these phenomena have been synthesized in the paradigms of the testicular dysgenesis syndrome in males (Skakkebeak et al. 2001) and the ovarian dysgenesis syndrome in females (Buck Louis et al. 2011a), providing conceptual frameworks for assessing environmental influences on human reproduction.

Persistent organic pollutants (POPs) are of major public health concern, given their long half-lives and tendency to bioaccumulate and biomagnify in wildlife and humans. Exposure to POPs, such as dioxins, organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), polybrominated biphenyls (PBBs), and polybrominated diphenyl ethers (PBDEs), particularly during the sensitive windows of human reproduction has been investigated in relation to a variety of reproductive outcomes, given the purported endocrine-disrupting properties of these chemicals (Nicolopoulou-Stamati and Pitsos 2001; Toft et al. 2004; Vested et al. 2014). Along with considerable experimental evidence suggesting the harmful effects of POPs on reproduction in terms of oocyte maturation and follicle physiology (Bhattacharya and Keating 2012; Pocar et al. 2003), a growing body of epidemiologic evidence has demonstrated that exposure to POPs may adversely affect human reproduction, possibly influencing reproductive hormones, menstrual cycles, semen quality, and couple fecundity among others (Buck Louis et al. 2013, 2016; Mumford et al. 2015; Nicolopoulou-Stamati and Pitsos 2001; Toft et al. 2004; Vested et al. 2014).

Previous reports have suggested that parental exposure to POPs may be associated with alterations in the SSR. For instance, in landmark studies among the resident population in Seveso, Italy following a chemical manufacturing plant explosion in 1976, paternal exposure to high levels of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) was found to be associated with the reversal of the SSR (i.e., an excess of female births) (Mocarelli et al. 1996, 2000). Several studies have also investigated PCBs in relation to the SSR, demonstrating equivocal findings on the association between this chemical class and the SSR and possible opposing directions toward infant sex depending upon partners (i.e., paternal versus maternal exposure) or hormonal activities (i.e., estrogenic versus anti-estrogenic) of PCB congeners (Nieminen et al. 2013; Taylor et al. 2007; Terrell et al. 2011). With regard to OCPs, the effects of exposure to dibromochloropropane (DBCP) (Potashnik et al. 1984; Potashnik and Porath 1995), dichlorodiphenyltrichloroethane (DDT) (Cocco et al. 2005, 2006; Salazar-García et al. 2004), and hexachlorobenzene (HCB) (Jarrell et al. 2002; Khanjani and Sim 2006) on the SSR have been evaluated in several studies, with paternal exposure to DBCP being somewhat consistently associated with the reversal of the SSR (Potashnik et al. 1984; Potashnik and Porath 1995). However, there have been few studies assessing both paternal and maternal preconception exposure to POPs in relation to the SSR as an approach to ensuring the temporal order of offspring sex determination. To investigate the potential effects of preconception exposure to POPs on human sex selection, we designed the Longitudinal Investigation of Fertility and the Environment (LIFE) Study of multiple classes of POPs and the SSR. By design, a total of 56 POPs measured prior to conception in both male and female partners were assessed in relation to the SSR in accordance with the couple-dependent nature of human conception.

2. Materials and methods

2.1. Study population

The LIFE Study is a prospective cohort study designed to investigate environmental influences on human fecundity and fertility, as previously described in detail (Buck Louis et al. 2011b). Briefly, 501 couples discontinuing contraception and trying for pregnancy were recruited from 16 counties in Michigan and Texas from 2005 to 2009, who were prospectively followed until pregnant or 12 months of attempting pregnancy. Women who became pregnant during the 12 months of follow-up were additionally followed to delivery or through a pregnancy loss. The eligibility criteria for participation were as follows: a) females aged 18–40 years and males aged 18 and older years; b) couples in a committed relationship; c) couples who were able to communicate in English or Spanish; d) females’ menstrual cycles ranging from 21 to 42 days; e) no use of injectable contraceptives within 12 months; and f) no history of physician-diagnosed infertility or sterilization procedures. Of the couples enrolled in the LIFE Study, 235 (46.9%) couples who had a singleton birth were used for the present study, excluding 2 (0.4%) couples who had multiple births and 264 (52.7%) couples without an observed live birth during the follow-up period. Institutional review board approvals were obtained from all collaborating institutions. Written informed consent was provided by all study participants prior to study participation.

2.2. Data collection

Baseline data were collected by research assistants in the couples’ home. Upon recruitment, the female partner provided a urine sample, which was used for a home pregnancy test to ensure that she was not pregnant. In-person interviews were conducted with each partner of the couple to ascertain socio-demographic characteristics (i.e., age, race/ethnicity, education, and annual household income) and reproductive history (i.e., parity and number of pregnancies fathered). Non-fasting blood (approximately 20 mL) was obtained from each partner of the couple for the quantification of serum concentrations of POPs and lipids. The blood samples were shipped on ice to the study’s laboratory and kept frozen at −20°C or colder until analysis. Couples who had a live birth during the follow-up period were asked to return standardized birth announcements following delivery to ascertain birth outcomes (i.e., infant sex, birth size, delivery mode, and date of birth).

2.3. Laboratory analysis

All analyses were conducted by the Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention. Specifically, couples’ serum concentrations (ng/g) were measured using isotope dilution high-resolution mass spectrometry for the following chemicals: a) 9 OCPs (HCB; β-hexachlorocyclohexane [β-HCH]; γ-hexachlorocyclohexane [γ-HCH]; oxychlordane; trans-nonachlor; o,p′-DDT; p,p′-DDT; p,p′-dichlorodiphenyldichloroethylene [p,p′-DDE]; and mirex); b) 1 PBB (PBB 153); c) 10 PBDEs (congeners #17, 28, 47, 66, 85, 99, 100, 153, 154, and 183); and d) 36 PCBs (congeners #28, 44, 49, 52, 66, 74, 87, 99, 101, 105, 110, 114, 118, 128, 138, 146, 149, 151, 153, 156, 157, 167, 170, 172, 177, 178, 180, 183, 187, 189, 194, 195, 196, 201, 206, and 209). Standard operating procedures were used for the quantification of a total of 56 serum POP concentrations, inclusive of ongoing quality assurance and control procedures (Sjödin et al. 2004). The limits of detection (LODs) varied by analyte, ranging from 0.003 to 0.01 ng/g. All machine-observed values for serum chemical concentrations were utilized for analysis without automatic substitution of concentrations below the LODs or lipid adjustment to preclude bias associated with such practices (Richardson and Ciampi 2003; Schisterman et al. 2006). Serum cotinine concentrations (ng/mL) were quantified using liquid chromatography-isotope dilution tandem mass spectrometry (Bernert et al. 1997) to assess baseline exposure to smoking. Serum lipids (ng/g) were quantified using commercially available enzymatic methods (Akins et al. 1989) and established calculation methods based on individual components including total cholesterol, free cholesterol, triglycerides, and phospholipids (Phillips et al. 1989).

2.4. Statistical analysis

In the descriptive phase of analysis, we assessed the distributions of all variables and inspected missing data and influential observations. Selected baseline characteristics of the study participants were evaluated by infant sex. Differences in continuous and categorical characteristics by infant sex were assessed using the nonparametric Wilcoxon test and Fisher’s exact test, respectively. Distributional properties of serum POP concentrations were summarized as geometric means (GMs) and 95% confidence intervals (CIs), along with selected percentiles (50th, 75th, 90th, 95th, and 99th). Differences in the GMs of serum POP concentrations by infant sex were assessed using the nonparametric Wilcoxon test.

In the analytic phase, we used modified Poisson regression models (Zou 2004) to estimate the relative risks (RRs) of a male live birth and corresponding 95% CIs for serum POP concentrations. In the models, serum POP concentrations were log-transformed to account for their skewed distribution and standardized by their standard deviation (SD) to aid in the interpretation of point estimates. Partner-specific models were run for maternal and paternal serum POP concentrations. Based on our review of the literature (Biggar et al. 1999; Chahnazarian 1988; Fukuda et al. 2002; Jacobsen et al. 1999; Kolk and Schnettler 2015; Koshy et al. 2010; Mathews and Hamilton 2005), we adjusted a priori for serum lipid (ng/g; continuous), age (years; continuous), maternal parity (nulliparous/parous; for maternal serum POP concentrations only), annual income (< $70,000/≥ $70,000), serum cotinine (ng/mL; continuous), and the sum of remaining chemicals in the relevant class of compounds. In addition, couple-based models, which simultaneously included both partners’ serum POP concentrations, were run to control for potential confounding by the other partner’s exposure when assessing each partner’s exposure in relation to the risk of a male live birth. As far as the correlation between maternal and paternal serum POP concentrations is concerned, significant mild-to-moderate correlations (Spearman’s rank correlation coefficient range, 0.14–0.59) were observed for 53 POPs (except for PCB congeners #149, 178, and 195), serving as a motivation for the use of couple-based models. Given the exploratory nature of this work, statistical significance was initially denoted by p-value < 0.05. We subsequently assessed the significance at the 0.0009 (approximately equal to 0.05/56 [the number of POPs examined]) level to adjust for multiple comparisons. All statistical analyses were performed using SAS Version 9.4 (SAS Institute Inc., Cary, NC, USA).

3. Results

Of the 235 live births, 116 (49.4%) were males and 119 (50.6%) were females, with the overall SSR of 0.97 (95% CI, 0.75–1.26) indicative of a female excess. The study cohort comprised predominantly non-Hispanic white and college-educated couples. The mean ages (± SD) of the female partners and the male partners were 29.8 (± 3.7) years and 31.5 (± 4.6) years, respectively. Approximately half of the female partners (53.2%) were parous and more than half of the male partners (57.5%) had previously fathered a pregnancy upon enrollment. Of the baseline characteristics examined, only one characteristic (i.e., paternal age) differed significantly by infant sex. Namely, the mean age (± SD) of men who fathered a boy (32.2 ± 5.1 years) was slightly higher than that of men who fathered a girl (30.8 ± 3.9 years; p-value, 0.03) (Table 1).

Table 1.

Baseline characteristics of the study participants by infant sex, 2005–2009

Characteristic Male (n=116)
n (%)		 Female (n=119)
n (%)
Maternal characteristic
 Age (years, mean ± SD) 30.0 ± 4.0 29.5 ± 3.4
 Serum lipids (ng/g, GM [95% CI]) 606 (587, 626) 610 (591, 630)
 Serum cotinine (ng/mL, GM [95% CI]) 0.03 (0.02, 0.04) 0.04 (0.02, 0.08)
 Parity
  Nulliparous 58 (50.4) 51 (43.2)
  Parous 57 (49.6) 67 (56.8)
 Annual income ($)
  < 70,000 27 (23.9) 32 (27.6)
  ≥ 70,000 86 (76.1) 84 (72.4)
 Education
  ≤ High school graduate/GED 5 (4.4) 4 (3.4)
  Some college/technical school 13 (11.4) 14 (11.8)
  College graduate or higher 96 (84.2) 101 (84.9)
 Race/ethnicity
  Non-Hispanic white 92 (80.7) 102 (85.7)
  Non-Hispanic black 2 (1.8) 1 (0.8)
  Hispanic 13 (11.4) 7 (5.9)
  Other 7 (6.1) 9 (7.6)
Paternal characteristic
 Age (years, mean ± SD) 32.2 ± 5.1* 30.8 ± 3.9*
 Serum lipids (ng/g, GM [95% CI]) 696 (668, 725) 706 (672, 742)
 Serum cotinine (ng/mL, GM [95% CI]) 0.08 (0.04, 0.15) 0.12 (0.06, 0.23)
 Number of pregnancies fathered
  0 46 (43.0) 48 (42.1)
  ≥ 1 61 (57.0) 66 (57.9)
 Annual income ($)
  < 70,000 25 (21.9) 36 (30.5)
  ≥ 70,000 89 (78.1) 82 (69.5)
 Education
  ≤ High school graduate/GED 3 (2.6) 4 (3.4)
  Some college/technical school 34 (29.6) 23 (19.5)
  College graduate or higher 78 (67.8) 91 (77.1)
 Race/ethnicity
  Non-Hispanic white 91 (79.1) 105 (88.2)
  Non-Hispanic black 3 (2.6) 2 (1.7)
  Hispanic 13 (11.3) 8 (6.7)
  Other 8 (7.0) 4 (3.4)
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*

Bolded values indicate p-value < 0.05.

Abbreviations: CI, confidence interval; GED, General Educational Development; GM, geometric mean.

The distributions (GMs and 95% CIs) of serum POP concentrations by infant sex are presented in Table 2. Selected percentiles (50th, 75th, 90th, 95th, and 99th) of serum POP concentrations are presented in Supplementary Table 1. Most couples (≥ 99%) had serum POP concentrations above the LOD for 2 OCPs (i.e., HCB and p,p′-DDE), 3 PBDEs (i.e., congeners #47, 100, and 153), and 5 PCBs (i.e., congeners #74, 118, 138, 153, and 180). Of the 9 OCPs, p,p′-DDE had the highest GM concentrations (for female partners, 0.58 ng/g [95% CI, 0.53–0.63]; for male partners, 0.75 ng/g [95% CI, 0.70–0.81]). The PBDE congener with the highest GM concentrations was PBDE 47 (for female partners, 0.12 ng/g [95% CI, 0.10–0.13]; for male partners, 0.11 ng/g [95% CI, 0.10–0.13]). Of the 36 PCB congeners, PCB 153 had the highest GM concentrations (for female partners, 0.04 ng/g [95% CI, 0.04–0.05]; for male partners, 0.06 ng/g [95% CI, 0.05–0.06]). Serum POP concentrations differed significantly by infant sex for paternal p,p′-DDE, 2 paternal PBDE congeners (i.e., congeners #154 and 183), and 4 maternal PCB congeners (i.e., congeners #87, 156, 157, and 167) with slightly higher serum concentrations in boys than in girls before rounding to two or three decimal places, except for maternal PCB 157 (Table 2).

Table 2.

Geometric means (95% confidence intervals) of persistent environmental chemical concentrations by infant sex, 2005–2009

Chemical (ng/g) Maternal serum concentration (n=233) Paternal serum concentration (n=230)
LOD % < LOD Male
GM (95% CI)		 Female
GM (95% CI)		 LOD % < LOD Male
GM (95% CI)		 Female
GM (95% CI)
OCPs
 HCB 0.01 < 1 0.05 (0.04, 0.06) 0.05 (0.04, 0.05) 0.01 < 1 0.05 (0.05, 0.06) 0.06 (0.05, 0.06)
 β-HCH 0.01 60 0.02 (0.01, 0.02) 0.01 (0.01, 0.02) 0.01 55 0.02 (0.02, 0.02) 0.02 (0.01, 0.02)
 γ-HCH 0.01 100 0.004 (0.004, 0.005) 0.005 (0.005, 0.005) 0.01 100 0.005 (0.005, 0.006) 0.007 (0.007, 0.008)
 Oxychlordane 0.01 16 0.04 (0.03, 0.04) 0.03 (0.03, 0.04) 0.01 11 0.04 (0.04, 0.05) 0.04 (0.04, 0.05)
 trans-Nonachlor 0.01 3 0.05 (0.05, 0.06) 0.05 (0.04, 0.06) 0.01 2 0.07 (0.06, 0.08) 0.06 (0.06, 0.07)
 o,p′-DDT 0.01 100 0.003 (0.002, 0.003) 0.002 (0.002, 0.002) 0.01 100 0.003 (0.003, 0.003) 0.003 (0.003, 0.003)
 p,p′-DDT 0.01 60 0.01 (0.01, 0.01) 0.01 (0.01, 0.01) 0.01 48 0.01 (0.01, 0.02) 0.01 (0.01, 0.01)
 p,p′-DDE 0.01 < 1 0.65 (0.58, 0.74) 0.52 (0.47, 0.57) 0.01 < 1 0.82 (0.73, 0.91)* 0.69 (0.63, 0.75)*
 Mirex 0.01 82 0.008 (0.007, 0.01) 0.007 (0.006, 0.007) 0.01 58 0.01 (0.01, 0.01) 0.01 (0.01, 0.01)
PBB and PBDEs
 PBB 153 0.003 9 0.008 (0.007, 0.009) 0.008 (0.007, 0.01) 0.003 5 0.01 (0.009, 0.01) 0.01 (0.01, 0.01)
 PBDE 17 0.003 88 0.001 (0.001, 0.002) 0.001 (0.001, 0.001) 0.003 88 0.001 (0.001, 0.002) 0.001 (0.001, 0.002)
 PBDE 28 0.003 23 0.01 (0.009, 0.01) 0.009 (0.008, 0.01) 0.003 29 0.01 (0.008, 0.01) 0.009 (0.008, 0.01)
 PBDE 47 0.01 < 1 0.13 (0.10, 0.16) 0.11 (0.09, 0.13) 0.01 1 0.13 (0.10, 0.15) 0.10 (0.09, 0.12)
 PBDE 66 0.003 93 0.001 (0.001, 0.002) 0.001 (0.001, 0.001) 0.003 97 0.002 (0.001, 0.002) 0.001 (0.001, 0.001)
 PBDE 85 0.003 60 0.003 (0.002, 0.003) 0.002 (0.002, 0.003) 0.003 62 0.003 (0.002, 0.003) 0.002 (0.002, 0.003)
 PBDE 99 0.01 25 0.02 (0.02, 0.03) 0.02 (0.02, 0.02) 0.01 28 0.02 (0.02, 0.03) 0.02 (0.02, 0.02)
 PBDE 100 0.003 < 1 0.03 (0.02, 0.03) 0.02 (0.02, 0.03) 0.003 < 1 0.03 (0.02, 0.03) 0.02 (0.02, 0.03)
 PBDE 153 0.003 < 1 0.05 (0.04, 0.05) 0.05 (0.04, 0.06) 0.003 < 1 0.07 (0.05, 0.08) 0.07 (0.06, 0.09)
 PBDE 154 0.003 62 0.003 (0.002, 0.004) 0.002 (0.002, 0.003) 0.003 65 0.003 (0.002, 0.004)* 0.003 (0.002, 0.003)*
 PBDE 183 0.003 83 0.002 (0.001, 0.002) 0.002 (0.001, 0.002) 0.003 74 0.002 (0.002, 0.002)* 0.002 (0.002, 0.002)*
PCBs
 PCB 28 0.008 67 0.007 (0.006, 0.008) 0.006 (0.005, 0.007) 0.009 76 0.006 (0.005, 0.007) 0.005 (0.004, 0.006)
 PCB 44 0.003 89 0.002 (0.002, 0.002) 0.002 (0.002, 0.002) 0.003 91 0.002 (0.002, 0.002) 0.002 (0.002, 0.002)
 PCB 49 0.003 100 0.0005 (0.0004, 0.0006) 0.0006 (0.0005, 0.0007) 0.003 100 0.0006 (0.0005, 0.0007) 0.0005 (0.0005, 0.0006)
 PCB 52 0.004 98 0.001 (0.0009, 0.001) 0.001 (0.0008, 0.001) 0.004 97 0.001 (0.001, 0.002) 0.001 (0.001, 0.001)
 PCB 66 0.003 38 0.003 (0.003, 0.004) 0.003 (0.003, 0.003) 0.003 56 0.003 (0.002, 0.003) 0.003 (0.002, 0.003)
 PCB 74 0.003 < 1 0.01 (0.01, 0.02) 0.01 (0.01, 0.01) 0.003 1 0.01 (0.01, 0.02) 0.01 (0.01, 0.02)
 PCB 87 0.003 93 0.002 (0.001, 0.002)* 0.001 (0.001, 0.002)* 0.003 94 0.002 (0.002, 0.002) 0.002 (0.001, 0.002)
 PCB 99 0.003 2 0.01 (0.01, 0.01) 0.01 (0.009, 0.01) 0.003 2 0.01 (0.01, 0.01) 0.01 (0.01, 0.01)
 PCB 101 0.003 71 0.002 (0.002, 0.003) 0.002 (0.002, 0.003) 0.003 63 0.003 (0.003, 0.003) 0.003 (0.002, 0.003)
 PCB 105 0.003 26 0.004 (0.004, 0.004) 0.004 (0.003, 0.004) 0.003 31 0.004 (0.004, 0.004) 0.004 (0.003, 0.004)
 PCB 110 0.003 90 0.001 (0.001, 0.002) 0.001 (0.001, 0.002) 0.003 90 0.002 (0.001, 0.002) 0.001 (0.001, 0.002)
 PCB 114 0.003 90 0.002 (0.001, 0.002) 0.002 (0.001, 0.002) 0.003 91 0.002 (0.001, 0.002) 0.002 (0.001, 0.002)
 PCB 118 0.003 < 1 0.02 (0.02, 0.02) 0.02 (0.01, 0.02) 0.003 < 1 0.02 (0.02, 0.02) 0.02 (0.02, 0.02)
 PCB 128 0.003 98 0.002 (0.002, 0.002) 0.003 (0.003, 0.004) 0.003 99 0.003 (0.003, 0.004) 0.002 (0.001, 0.002)
 PCB 138 0.003 1 0.03 (0.03, 0.04) 0.03 (0.03, 0.03) 0.003 < 1 0.04 (0.04, 0.04) 0.04 (0.03, 0.04)
 PCB 146 0.003 20 0.006 (0.005, 0.007) 0.005 (0.005, 0.006) 0.003 10 0.008 (0.007, 0.009) 0.007 (0.007, 0.008)
 PCB 149 0.003 100 0.001 (0.001, 0.002) 0.001 (0.001, 0.002) 0.003 100 0.001 (0.001, 0.002) 0.001 (0.001, 0.002)
 PCB 151 0.003 99 0.002 (0.001, 0.002) 0.002 (0.001, 0.002) 0.003 98 0.002 (0.002, 0.002) 0.003 (0.002, 0.003)
 PCB 153 0.003 < 1 0.05 (0.04, 0.05) 0.04 (0.04, 0.05) 0.003 < 1 0.06 (0.05, 0.07) 0.06 (0.05, 0.06)
 PCB 156 0.003 12 0.006 (0.006, 0.007)* 0.006 (0.005, 0.007)* 0.003 8 0.008 (0.007, 0.009) 0.008 (0.007, 0.009)
 PCB 157 0.003 78 0.002 (0.002, 0.002)* 0.002 (0.002, 0.003)* 0.003 70 0.002 (0.002, 0.003) 0.003 (0.002, 0.003)
 PCB 167 0.003 79 0.003 (0.003, 0.003)* 0.003 (0.003, 0.003)* 0.003 75 0.003 (0.003, 0.003) 0.003 (0.003, 0.003)
 PCB 170 0.003 2 0.01 (0.01, 0.02) 0.01 (0.01, 0.01) 0.003 1 0.02 (0.02, 0.02) 0.02 (0.02, 0.02)
 PCB 172 0.003 79 0.003 (0.002, 0.003) 0.002 (0.002, 0.003) 0.003 63 0.003 (0.003, 0.004) 0.003 (0.003, 0.004)
 PCB 177 0.003 57 0.003 (0.003, 0.003) 0.003 (0.003, 0.003) 0.003 41 0.003 (0.003, 0.004) 0.004 (0.003, 0.004)
 PCB 178 0.003 63 0.003 (0.003, 0.004) 0.003 (0.003, 0.003) 0.003 36 0.004 (0.004, 0.005) 0.004 (0.004, 0.005)
 PCB 180 0.003 < 1 0.03 (0.03, 0.04) 0.03 (0.03, 0.03) 0.003 < 1 0.05 (0.04, 0.05) 0.05 (0.04, 0.05)
 PCB 183 0.003 30 0.005 (0.004, 0.005) 0.005 (0.004, 0.005) 0.003 17 0.006 (0.005, 0.006) 0.006 (0.005, 0.006)
 PCB 187 0.003 7 0.01 (0.01, 0.01) 0.01 (0.009, 0.01) 0.003 5 0.02 (0.01, 0.02) 0.02 (0.01, 0.02)
 PCB 189 0.003 99 0.001 (0.001, 0.002) 0.001 (0.001, 0.001) 0.003 97 0.002 (0.002, 0.002) 0.001 (0.001, 0.002)
 PCB 194 0.003 14 0.008 (0.007, 0.009) 0.007 (0.006, 0.008) 0.003 8 0.01 (0.01, 0.01) 0.01 (0.009, 0.01)
 PCB 195 0.003 75 0.003 (0.003, 0.003) 0.003 (0.002, 0.003) 0.003 64 0.003 (0.003, 0.004) 0.003 (0.003, 0.004)
 PCB 196 0.003 9 0.008 (0.007, 0.009) 0.007 (0.007, 0.008) 0.003 3 0.01 (0.01, 0.01) 0.01 (0.009, 0.01)
 PCB 201 0.003 14 0.007 (0.007, 0.008) 0.007 (0.006, 0.008) 0.003 6 0.01 (0.009, 0.01) 0.01 (0.009, 0.01)
 PCB 206 0.003 28 0.004 (0.004, 0.004) 0.004 (0.003, 0.004) 0.003 9 0.006 (0.005, 0.007) 0.006 (0.005, 0.007)
 PCB 209 0.003 77 0.002 (0.002, 0.002) 0.002 (0.002, 0.002) 0.003 52 0.003 (0.003, 0.003) 0.003 (0.002, 0.003)
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Note: Of 235 couples with a singleton birth, 2 mothers and 5 fathers without serum chemical concentrations were excluded.

*

Bolded values indicate p-value < 0.05.

Abbreviations: CI, confidence interval; GM, geometric mean; LOD, limit of detection; OCP, organochlorine pesticide; HCB, hexachlorobenzene; HCH, hexachlorocyclohexane; DDT, dichlorodiphenyltrichloroethane; DDE, dichlorodiphenyldichloroethylene; PBB, polybrominated biphenyl; PBDE, polybrominated diphenyl ether; PCB, polychlorinated biphenyl.

Table 3 presents the RRs of a male birth by maternal and paternal serum POP concentrations, only for POPs with any significant associations with a male birth across the models. See Supplementary Table 2 for corresponding estimates for all other POPs examined. When couples’ serum POP concentrations were modeled jointly in combination with other covariates, significant associations between select POPs and the SSR were noted. Specifically, of the 56 POPs examined, maternal PCB 128 and paternal HCB were significantly associated with an excess of female births (adjusted RRs, 0.75 [95% CI, 0.60–0.94] and 0.81 [95% CI, 0.68–0.97] per 1 SD increase in log-transformed serum chemical concentrations, respectively). On the other hand, maternal mirex, paternal PCB 128, and paternal p,p′-DDE were significantly associated with an excess of male births (adjusted RR range, 1.10–1.22 per 1 SD increase in log-transformed serum chemical concentrations). However, when the significance was assessed at the 0.0009 level, only maternal mirex remained significantly associated with the SSR (Table 3).

Table 3.

Persistent environmental chemicalsa and the relative risks (95% confidence intervals) of a male birth by partner, 2005–2009

Chemical (ng/g) Partner-specific model Couple-based model
Model Ab
RR (95% CI)		 Model Bc
RR (95% CI)		 Model Ab
RR (95% CI)		 Model Bc
RR (95% CI)
Maternal serum concentrations
 β-HCH 1.06 (1.03, 1.10)* 1.00 (0.92, 1.08) 1.04 (0.97, 1.11) 0.99 (0.91, 1.09)
 p,p′-DDT 1.08 (1.04, 1.12)** 1.01 (0.91, 1.12) 1.08 (0.93, 1.25) 1.04 (0.88, 1.23)
 p,p′-DDE 1.17 (1.08, 1.26)** 1.16 (1.02, 1.31)* 1.10 (0.98, 1.23) 1.13 (0.99, 1.28)
 Mirex 1.10 (1.06, 1.15)** 1.09 (1.05, 1.13)** 1.10 (1.06, 1.15)** 1.10 (1.04, 1.15)**
 PBDE 17 1.07 (1.03, 1.12)* 1.02 (0.94, 1.11) 1.09 (1.00, 1.19) 1.07 (0.96, 1.20)
 PBDE 28 1.09 (1.01, 1.17)* 1.03 (0.92, 1.16) 1.09 (1.01, 1.17)* 1.04 (0.92, 1.19)
 PBDE 47 1.12 (1.01, 1.24)* 1.22 (0.94, 1.57) 1.06 (0.93, 1.22) 1.06 (0.79, 1.42)
 PBDE 85 1.11 (1.02, 1.20)* 1.23 (0.99, 1.53) 1.11 (0.99, 1.24) 1.19 (0.95, 1.48)
 PBDE 99 1.11 (1.01, 1.22)* 1.20 (1.01, 1.44)* 1.12 (1.01, 1.24)* 1.16 (0.96, 1.40)
 PBDE 154 1.11 (1.02, 1.21)* 1.27 (1.04, 1.56)* 1.11 (1.00, 1.23)* 1.21 (0.98, 1.48)
 PCB 28 1.05 (1.04, 1.06)** 1.04 (0.99, 1.10) 0.58 (0.01, 26.2) 0.69 (0.01, 39.5)
 PCB 44 1.05 (1.04, 1.06)** 1.05 (0.99, 1.12) 1.97 (0.54, 7.22) 1.86 (0.49, 7.09)
 PCB 49 1.04 (1.03, 1.06)** 1.04 (0.98, 1.11) 0.80 (0.22, 2.93) 0.76 (0.22, 2.67)
 PCB 52 1.05 (1.04, 1.06)** 1.05 (0.99, 1.11) 1.60 (0.42, 6.06) 1.64 (0.45, 6.06)
 PCB 66 1.05 (1.04, 1.06)** 1.05 (0.99, 1.11) 1.15 (0.20, 6.08) 0.99 (0.17, 5.94)
 PCB 74 1.05 (1.02, 1.07)** 1.04 (0.97, 1.11) 0.95 (0.65, 1.39) 0.66 (0.43, 1.03)
 PCB 87 1.10 (1.03, 1.18)* 1.11 (1.00, 1.23)* 1.13 (1.01, 1.26)* 1.10 (0.98, 1.25)
 PCB 128 0.84 (0.65, 1.08) 0.81 (0.63, 1.04) 0.75 (0.60, 0.95)* 0.75 (0.60, 0.94)*
 PCB 157 1.12 (0.99, 1.26) 1.08 (0.93, 1.25) 1.12 (0.99, 1.26)* 1.10 (0.93, 1.30)
Paternal serum concentrations
 HCB 0.87 (0.72, 1.04) 0.81 (0.68, 0.96) 0.85 (0.71, 1.02) 0.81 (0.68, 0.97)*
 β-HCH 1.07 (1.04, 1.10)** 1.09 (1.01, 1.18)* 1.04 (0.97, 1.11) 1.06 (0.98, 1.16)
 p,p′-DDE 1.17 (1.09, 1.26)** 1.28 (1.10, 1.49)* 1.11 (0.99, 1.24) 1.22 (1.03, 1.44)*
 PBDE 47 1.11 (0.99, 1.24) 1.29 (1.06, 1.56)* 1.07 (0.92, 1.24) 1.26 (1.00, 1.58)
 PCB 28 1.05 (1.04, 1.06)** 1.05 (1.00, 1.11) 1.81 (0.04, 84.9) 1.50 (0.02, 90.5)
 PCB 44 1.05 (1.03, 1.06)** 1.05 (1.00, 1.11) 0.53 (0.14, 1.95) 0.55 (0.14, 2.13)
 PCB 49 1.04 (1.03, 1.06)** 1.05 (1.00, 1.11) 1.30 (0.35, 4.78) 1.34 (0.38, 4.76)
 PCB 52 1.04 (1.03, 1.06)** 1.05 (0.99, 1.10) 0.65 (0.17, 2.49) 0.62 (0.17, 2.33)
 PCB 66 1.05 (1.04, 1.06)** 1.06 (1.00, 1.11)* 0.91 (0.15, 5.43) 1.04 (0.17, 6.38)
 PCB 74 1.05 (1.03, 1.07)** 1.07 (1.00, 1.13)* 1.11 (0.75, 1.63) 1.54 (0.99, 2.41)
 PCB 128 1.00 (0.87, 1.14) 1.02 (0.86, 1.21) 1.18 (1.04, 1.33)* 1.21 (1.03, 1.42)*
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Note: Modified Poisson regression models were used to estimate the relative risks of a male birth (Zou, 2004). All point and interval estimates were rounded to two decimal places. In the couple-based models, both maternal and paternal serum POP concentrations were included simultaneously in combination with other covariates.

a

Restricted to chemicals with any significant associations with a male birth across the models.

b

Adjusted for serum lipid (ng/g; continuous).

c

Adjusted for serum lipid (ng/g; continuous), age (years; continuous; maternal age and delta [paternal age - maternal age] were included in the couple-based models), maternal parity (nulliparous/parous; for maternal serum chemical concentrations only), annual income (< $70,000/≥ $70,000), serum cotinine (ng/mL; continuous), and the sum of remaining chemicals in the relevant class of compounds.

*

Bolded values indicate p-value < 0.05.

**

Bolded values indicate p-value < 0.0009 (approximately equal to 0.05/56 [the number of persistent environmental chemicals examined]).

Abbreviations: CI, confidence interval; RR, relative risk; HCB, hexachlorobenzene; HCH, hexachlorocyclohexane; DDT, dichlorodiphenyltrichloroethane; DDE, dichlorodiphenyldichloroethylene; PBDE, polybrominated diphenyl ether; PCB, polychlorinated biphenyl.

4. Discussion

In this population-based prospective cohort study, we found no conclusive evidence supporting an association between parental preconception exposure to POPs and the SSR. In fact, in our exploratory analysis of multiple classes of POPs, 2 serum POP concentrations in mothers (i.e., mirex and PCB 128) and 3 (i.e., HCB, p,p′-DDE, and PCB 128) in fathers were significantly associated with an excess of male or female births, when couples’ serum POP concentrations were modeled jointly in combination with other covariates. However, of note is the lack of robustness in the significant findings depending upon model specification or statistical methods used, possibly indicating uncertain associations of these select POPs with the SSR. Furthermore, when we adjusted for multiple comparisons by assessing the significance at the 0.0009 level, only the association observed for maternal serum mirex concentrations and an excess of male births remained significant. When the tertiles of serum POP concentrations were used in the couple-based multivariate-adjusted model, a possible dose-response relation was noted for maternal mirex (2nd versus 1st tertile, adjusted RR, 1.06 [95% CI, 0.74–1.52]; 3rd versus 1st tertile, adjusted RR, 1.33 [95% CI, 0.91–1.92]; data not shown), although not significant. Still, it is worth noting that serum mirex concentrations were below the LOD in 82% of the female partners. Meanwhile, serum mirex concentrations in the U.S. general population from the National Health and Nutrition Examination Survey (NHANES) were generally below the LOD (somewhere between 75% and 90% of the population) during the comparable time period (Centers for Disease Control and Prevention 2017). As far as we know from the literature, our study is the first report on the association between maternal serum mirex concentrations and the SSR, underscoring the need for corroboration through further research on this topic.

Our study appears to be in line with some but not all previous reports suggesting significant associations between select POPs and the SSR. In a recent review of more than 100 studies on environmental and occupational toxicants and the SSR, Terrell et al. (2011) concluded that paternal exposure to dioxins may be associated with a decreased SSR, whereas paternal exposure to PCBs may be associated with an increased SSR. On the other hand, in a systematic review of 15 studies on PCBs and the SSR, Nieminen et al. (2013) found no strong or moderate indication that parental exposure to PCBs altered the SSR from the historical reference range. In fact, a small number of studies have suggested that maternal serum PCB concentrations may be associated with a decreased SSR (Hertz-Picciotto et al. 2008; Weisskopf et al. 2003). In a retrospective cohort of 173 mothers with a live birth from the Great Lakes region of the United States between 1970 and 1995, the adjusted odds ratio (OR) for a male birth among mothers in the highest quintile of serum PCB concentrations was 0.18 (95% CI, 0.06–0.59) compared with mothers in the lowest quintile (Weisskopf et al. 2003). A prospective cohort study of 339 pregnant women in the San Francisco Bay Area during the 1960s showed that the RR of a male birth decreased by 33% comparing women at the 90th percentile of a total of 11 PCBs with women at the 10th percentile (RR, 0.67; 95% CI, 0.48–0.94) (Hertz-Picciotto et al. 2008). Meanwhile, a preliminary study on maternal preconception exposure to PCBs and the SSR was suggestive of varying effects of PCB congeners on the SSR depending upon their hormonal activities (Taylor et al. 2007). Namely, in a cohort of 50 women with a live birth from the New York State Angler Cohort Study, maternal preconception exposure to estrogenic PCBs (congeners #4, 8, 15, 18, 31, 44, 47, 48, 52, 70, 77, 99, 101, 126, 136, 153, and 188) but not anti-estrogenic PCBs (congeners #77, 105, 114, 126, 156, and 169) was associated with an increased SSR, although the association did not reach statistical significance (Taylor et al. 2007).

In the present study, we found that only one out of the 36 PCB congeners examined (i.e., PCB 128 as a non-dioxin-like PCB) was significantly associated with the SSR in the couple-based multivariate-adjusted models, demonstrating opposing associations of this chemical with the SSR depending upon partners. Specifically, paternal PCB 128 was associated with an excess of male births, whereas maternal PCB 128 was associated with an excess of female births. However, it is noteworthy that serum PCB 128 concentrations were relatively low and below the LOD in 98% of the female partners and in 99% of the male partners. Likewise, serum PCB 128 concentrations in the U.S. general population from the NHANES were mostly below the LOD during the comparable time period (Centers for Disease Control and Prevention 2017). Furthermore, when we adjusted for multiple comparisons, the associations of maternal and paternal PCB 128 with the SSR were no longer significant (p-value ≥ 0.0009), indicative of the possibility of chance findings. Although we did not examine parental exposure to dioxins, we did assess the effects of dioxin-like PCBs (i.e., mono-ortho-substituted PCBs; congeners #105, 114, 118, 156, 157, 167, and 189) on the SSR, without noticing any significant associations. Of note, although not significant, some maternal estrogenic PCBs (e.g., congeners #44 and 52) were associated with an increased SSR (in the couple-based models, adjusted RRs, 1.86 [95% CI, 0.49–7.09] and 1.64 [95% CI, 0.45–6.06] per 1 SD increase in log-transformed serum chemical concentrations, respectively; Table 3), consistent with a previous report on maternal estrogenic PCBs and the SSR (Taylor et al. 2007).

Although our study is the first investigation known to us on the association between mirex and the SSR, environmental or occupational exposure to other OCPs such as HCB and DDT has been assessed in relation to the SSR in some previous studies. For instance, exposure to HCB was not found to be associated with alterations in the SSR in a study using the Turkish national data from 1935 to 1990 (Jarrell et al. 2002) or in a cohort of primiparous women enrolled in the 1990s in Austria (Khanjani and Sim 2006). In addition, exposure to DDT in the anti-malaria campaign in some countries such as Italy (Cocco et al. 2005, 2006) and Mexico (Salazar-García et al. 2004) has been investigated in relation to the SSR, demonstrating equivocal findings on the effects of exposure to DDT (as measured by estimated concentrations of p,p′-DDE [the most persistent metabolite of DDT] in fat) on the SSR. Meanwhile, our study showed that paternal serum HCB concentrations were significantly associated with a decreased SSR (in the couple-based model, adjusted RR, 0.81 [95% CI, 0.68–0.97] per 1 SD increase in log-transformed serum chemical concentrations; p-value ≥ 0.0009; Table 3), consistent with some previous studies indicating male-mediated effects of select chemicals (e.g., TCDD and DBCP) on the reversal of the SSR (Mocarelli et al. 1996, 2000; Potashnik et al. 1984; Potashnik and Porath 1995). Contrarily, paternal serum concentrations of p,p′-DDE were found to be significantly associated with an increased SSR (in the couple-based model, adjusted RR, 1.22 [95% CI, 1.03–1.44] per 1 SD increase in log-transformed serum chemical concentrations; p-value ≥ 0.0009; Table 3) in our study, although we cannot rule out the possibility of a chance finding.

In the present study, no statistically significant associations of PBB 153 and PBDEs with the SSR were observed. While some maternal PBDEs (i.e., congeners #28, 99, and 154) showed significant associations with an excess of male births in the couple-based crude models (RR range, 1.09–1.12 per 1 SD increase in log-transformed serum chemical concentrations; Table 3), the associations no longer remained significant after the adjustment for covariates. When we further evaluated the effects of covariates on the associations between these PBDEs and the SSR in the couple-based multivariate-adjusted models, only delta (paternal age − maternal age) was found to be significantly associated with the risk of a male birth (adjusted RR, 1.04; 95% CI, 1.01–1.08; data not shown). To the best of our knowledge, there have been no previous studies investigating the association between serum PBDE concentrations and the SSR, underscoring the need for additional research on this topic. As for PBBs, in a cohort of 300 couples from the Michigan Long-Term PBB Study, combined parental exposure to PBBs increased the odds of a male birth, although the finding did not reach statistical significance (Terrell et al. 2009). Meanwhile, perfluoroalkyl and polyfluoroalkyl substances (PFASs), an emerging class of POPs, have been first evaluated in relation to the SSR in our previous study using data from the LIFE Study, suggesting paternal exposure to select PFASs (i.e., paternal N-methyl-perfluorooctane sulfonamidoacetic acid and perfluorononanoic acid) being associated with the reversal of the SSR (Bae et al. 2015).

While research efforts have been made to identify genetic (e.g., the SRY [sex-determining region Y] gene) and environmental determinants of offspring sex, the mechanistic underpinnings of human sex selection are still obscure. It has been thought that multiple factors in fathers (e.g., sperm Y:X chromosome ratio and intrinsic differences in size and swimming velocity between Y- and X-chromosome bearing sperm) and mothers (e.g., sperm selection within the female reproductive tract and differential survival of male and female embryos) may contribute to offspring sex determination (Almiñana et al. 2014; Davis et al. 2007; Jongbloet 2004; Tiido et al. 2005). One of the prevailing hypotheses on the SSR is the James’ hormonal hypothesis, which theorizes that parental hormone levels around the time of conception are partly responsible for alterations in the SSR (James 2008a, 2008b, 2012, 2013). According to this hypothesis, high levels of gonadal hormones, such as testosterone (of either parent) and estrogen (of mother), are associated with an excess of male births, whereas high levels of gonadotropins, such as follicle-stimulating hormone (FSH) and luteinizing hormone (LH), of either parent are associated with an excess of female births (James 2013). Given the purported endocrine-disrupting effects of POPs, some of our findings (e.g., maternal estrogenic PCBs and an increased SSR [although not significant]; paternal HCB [Ralph et al. 2003] and a decreased SSR) appear to be congruent with the hormonal hypothesis, whereas others (e.g., paternal p,p′-DDE [Ayotte et al. 2001; Martin et al. 2002] and an increased SSR) do not.

Existing evidence on the hormonal activities of mirex is conflicting, making it somewhat challenging to interpret our findings on maternal serum mirex concentrations and an increased SSR based on the hormonal hypothesis. For instance, when tested by the E-SCREEN assay, mirex did not show estrogenic activity without inducing the proliferation of MCF-7 human breast cancer cells (Soto et al. 1995). In an androgen-responsive reporter gene assay, mirex did not antagonize the effect of 5α-dihydrotestosterone, exhibiting no interaction with the androgen receptor (Schrader and Cooke 2000). Along with its questionable in vitro estrogenic or anti-androgenic effects, mirex was not found to be significantly associated with the levels of sex hormones such as estradiol, FSH, and LH among 210 premenopausal women, although an inverse association between LH and serum mirex concentrations was noted among 77 peri- and postmenopausal women in a cross-sectional study conducted in Brazil (Freire et al. 2014). On the other hand, in a population-based case-control study conducted in the United States, serum mirex concentrations were associated with an increased risk of endometriosis, an estrogen-dependent gynecologic disorder (Upson et al. 2013). In a nested case-control study of 48 newborns with diagnosis of cryptorchidism and/or hypospadias and 114 controls, mirex measured in placenta tissues was significantly associated with an increased risk of genitourinary malformations, suggesting that exposure to mirex may provoke an unbalanced androgen/estrogen ratio and lead to abnormal male sexual differentiation (Fernandez et al. 2007; Skakkebaek et al. 2001). As such, it is difficult to interpret the observed findings on POPs and the SSR simply based on the hormonal hypothesis, partly because these chemicals may have more than one mode of action (e.g., both estrogenic and anti-androgenic) and exhibit different modes of action at different doses. Although we assessed each chemical in relation to the SSR while adjusting for the sum of remaining chemicals in the relevant class of compounds, it is important to keep in mind that chemical mixtures may act together to disturb the endocrine system. In addition, the background levels of endogenous hormones in males and females may play a role in the mode(s) of action of a given chemical, possibly explaining the discrepancy in the findings on POPs and the SSR by partner. In consideration of toxicokinetics and toxicodynamics, it is also worth noting that different metabolites may have different hormonal activities compared with their parent compound (Andersson et al. 2016). Together with taking all these factors that may influence the hormonal milieu into account, possible non-hormonal mechanisms by which exposure to POPs alters the SSR (e.g., sperm abnormalities) deserve more research attention (Bae et al. 2017a; Fukuda et al. 1998).

The strengths of the present study include the quantification of serum POP concentrations prior to conception, along with the prospective cohort design. Our couple-based cohort enabled us to incorporate both partners’ serum POP concentrations into the same models when assessing a couple-dependent birth outcome. Given that POPs may have different endocrine-disrupting effects for men and women, it is necessary to assess each partner’s possible role in determining offspring sex while controlling for the other partner’s. However, the major limitations of the present study should be considered when interpreting the study results. We were unable to evaluate the primary sex ratio or sex ratio at conception due to the difficulty in measuring conception at the population level. With the absence of data on preconception hormone levels, we were unable to fully explore the purported hormonal activities of POPs and their associations with the SSR. The possibility of residual confounding or model misspecification should be taken into account, given the uncertainty as to factors influencing the SSR. Although we believe that our cohort is one of the largest couple-based cohorts with preconception recruitment, its sample size may be relatively small with regard to the detection of variability in the SSR. As we undertook multiple tests to assess a number of POPs in relation to the SSR, the possibility of chance findings cannot be ruled out. Given the sampling of couples with planned pregnancy, the study results may not be generalizable to couples with unplanned pregnancy or the general population.

5. Conclusions

In a comprehensive evaluation of multiple classes of POPs in relation to the SSR, we found that specific POPs (i.e., mirex and PCB 128 in mothers; HCB, p,p′-DDE, and PCB 128 in fathers) were significantly associated with alterations in the SSR, consistent with some but not all earlier findings on POPs and the SSR. However, the significant findings noted in our study await corroboration, given the absence of previous investigation on certain POPs (e.g., mirex and PBDEs) and the inconsistencies over the effects of each chemical on offspring sex determination. Furthermore, our findings need to be interpreted with caution, given our exploratory analytic approach and major limitations of the study. With the lack of conclusive evidence on the association between parental preconception exposure to POPs and the SSR, we wish to stress the need for further confirmatory research particularly focusing on the mechanistic underpinnings of human sex selection. Preferably, larger couple-based preconception cohort studies, which allow the measurement of time-sensitive exposures for couples, are warranted to elucidate the effects of POPs on human sex selection, as a parentally-mediated reproductive event. Such research efforts will facilitate understanding of the potential health implications of exposure to these ubiquitous chemicals at environmentally relevant doses.

Supplementary Material

supplement

Highlights.

  • Recent declines in the SSR in some countries may be attributed to exposure to POPs.

  • Maternal PCB 128 and paternal HCB were associated with a female excess.

  • Maternal mirex and paternal PCB 128 and p,p′-DDE were associated with a male excess.

  • These findings await corroboration given the exploratory design of this study.

Acknowledgments

Funding

This study was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (contracts #N01-HD-3-3355, N01-HD-3-3356, N01-HD-3-3358).

List of abbreviations

CI

confidence interval

DBCP

dibromochloropropane

DDE

dichlorodiphenyldichloroethylene

DDT

dichlorodiphenyltrichloroethane

FSH

follicle-stimulating hormone

GED

General Educational Development

GM

geometric mean

HCB

hexachlorobenzene

HCH

hexachlorocyclohexane

LH

luteinizing hormone

LIFE

Longitudinal Investigation of Fertility and the Environment

LOD

limit of detection

NHANES

National Health and Nutrition Examination Survey

OCP

organochlorine pesticide

OR

odds ratio

PBB

polybrominated biphenyl

PBDE

polybrominated diphenyl ether

PCB

polychlorinated biphenyl

PFAS

perfluoroalkyl and polyfluoroalkyl substance

POP

persistent organic pollutant

RR

relative risk

SD

standard deviation

SSR

secondary sex ratio

TCDD

2,3,7,8-tetrachlorodibenzo-p-dioxin

Footnotes

Ethical statement

Institutional review board approvals were obtained from all collaborating institutions. Written informed consent was provided by all study participants prior to study participation.

Conflicts of interest:

None.

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References

  1. Akins JR, Waldrep K, Bernert JT., Jr The estimation of total serum lipids by a completely enzymatic ‘summation’ method. Clin Chim Acta. 1989;184:219–226. doi: 10.1016/0009-8981(89)90054-5. [DOI] [PubMed] [Google Scholar]
  2. Almiñana C, Caballero I, Heath PR, Maleki-Dizaji S, Parrilla I, Cuello C, et al. The battle of the sexes starts in the oviduct: modulation of oviductal transcriptome by X and Y-bearing spermatozoa. BMC Genomics. 2014;15:293. doi: 10.1186/1471-2164-15-293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Andersson AM, Bay K, Frederiksen H, Skakkebaek NE. Endocrine disrupters: we need research, biomonitoring and action. Andrology. 2016;4:556–560. doi: 10.1111/andr.12244. [DOI] [PubMed] [Google Scholar]
  4. Ayotte P, Giroux S, Dewailly E, Hernández Avila M, Farias P, et al. DDT spraying for malaria control and reproductive function in Mexican men. Epidemiology. 2001;12:366–367. doi: 10.1097/00001648-200105000-00022. [DOI] [PubMed] [Google Scholar]
  5. Bae J, Kim S, Chen Z, Eisenberg ML, Buck Louis GM. Human semen quality and the secondary sex ratio. Asian J Androl. 2017a;19:374–381. doi: 10.4103/1008-682X.173445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bae J, Kim S, Schisterman EF, Boyd Barr D, Buck Louis GM. Maternal and paternal serum concentrations of perfluoroalkyl and polyfluoroalkyl substances and the secondary sex ratio. Chemosphere. 2015;133:31–40. doi: 10.1016/j.chemosphere.2015.03.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bae J, Lynch CD, Kim S, Sundaram R, Sapra KJ, Buck Louis GM. Preconception stress and the secondary sex ratio in a population-based preconception cohort. Fertil Steril. 2017b;107:714–722. doi: 10.1016/j.fertnstert.2016.12.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bernert JT, Jr, Turner WE, Pirkle JL, Sosnoff CS, Akins JR, Waldrep MK, et al. Development and validation of sensitive method for determination of serum cotinine in smokers and nonsmokers by liquid chromatography/atmospheric pressure ionization tandem mass spectrometry. Clin Chem. 1997;43:2281–2291. [PubMed] [Google Scholar]
  9. Bhattacharya P, Keating AF. Impact of environmental exposures on ovarian function and role of xenobiotic metabolism during ovotoxicity. Toxicol Appl Pharmacol. 2012;261:227–235. doi: 10.1016/j.taap.2012.04.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Biggar RJ, Wohlfahrt J, Westergaard T, Melbye M. Sex ratios, family size, and birth order. Am J Epidemiol. 1999;150:957–962. doi: 10.1093/oxfordjournals.aje.a010104. [DOI] [PubMed] [Google Scholar]
  11. Buck Louis GM, Barr DB, Kannan K, Chen Z, Kim S, Sundaram R. Paternal exposures to environmental chemicals and time-to-pregnancy: overview of results from the LIFE study. Andrology. 2016;4:639–647. doi: 10.1111/andr.12171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Buck Louis GM, Cooney MA, Peterson CM. The ovarian dysgenesis syndrome. J Dev Orig Health Dis. 2011a;2:25–35. [Google Scholar]
  13. Buck Louis GM, Platt RW. Reproductive and Perinatal Epidemiology. 1. New York: Oxford University Press; 2011. [Google Scholar]
  14. Buck Louis GM, Schisterman EF, Sweeney AM, Wilcosky TC, Gore-Langton RE, Lynch CD, et al. Designing prospective cohort studies for assessing reproductive and developmental toxicity during sensitive windows of human reproduction and development – the LIFE Study. Paediatr Perinat Epidemiol. 2011b;25:413–424. doi: 10.1111/j.1365-3016.2011.01205.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Buck Louis GM, Sundaram R, Schisterman EF, Sweeney AM, Lynch CD, Gore-Langton RE, et al. Persistent environmental pollutants and couple fecundity: the LIFE study. Environ Health Perspect. 2013;121:231–236. doi: 10.1289/ehp.1205301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Centers for Disease Control and Prevention. Fourth National Report on Human Exposure to Environmental Chemicals, Updated Tables, January 2017. Atlanta, GA: Centers for Disease Control and Prevention; 2017. [Google Scholar]
  17. Chahnazarian A. Determinants of the sex ratio at birth: review of recent literature. Soc Biol. 1988;35:214–235. doi: 10.1080/19485565.1988.9988703. [DOI] [PubMed] [Google Scholar]
  18. Cocco P, Fadda D, Ibba A, Melis M, Tocco MG, Atzeri S, et al. Reproductive outcomes in DDT applicators. Environ Res. 2005;98:120–126. doi: 10.1016/j.envres.2004.09.007. [DOI] [PubMed] [Google Scholar]
  19. Cocco P, Fadda D, Melis M. Reproductive outcomes following environmental exposure to DDT. Reprod Toxicol. 2006;22:5–7. doi: 10.1016/j.reprotox.2005.12.006. [DOI] [PubMed] [Google Scholar]
  20. Davis DL, Webster P, Stainthorpe H, Chilton J, Jones L, Doi R. Declines in sex ratio at birth and fetal deaths in Japan, and in U.S. whites but not African Americans. Environ Health Perspect. 2007;115:941–946. doi: 10.1289/ehp.9540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fernandez MF, Olmos B, Granada A, López-Espinosa MJ, Molina-Molina JM, Fernandez JM, et al. Human exposure to endocrine-disrupting chemicals and prenatal risk factors for cryptorchidism and hypospadias: a nested case-control study. Environ Health Perspect. 2007;115:S8–S14. doi: 10.1289/ehp.9351. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Freire C, Koifman RJ, Sarcinelli PN, Rosa AC, Clapauch R, Koifman S. Association between serum levels of organochlorine pesticides and sex hormones in adults living in a heavily contaminated area in Brazil. Int J Hyg Environ Health. 2014;217:370–378. doi: 10.1016/j.ijheh.2013.07.012. [DOI] [PubMed] [Google Scholar]
  23. Fukuda M, Fukuda K, Shimizu T, Andersen CY, Byskov AG. Parental periconceptional smoking and male: female ratio of newborn infants. Lancet. 2002;359:1407–1408. doi: 10.1016/S0140-6736(02)08362-9. [DOI] [PubMed] [Google Scholar]
  24. Fukuda M, Fukuda K, Shimizu T, Moller H. Decline in sex ratio at birth after Kobe earthquake. Hum Reprod. 1998;13:2321–2322. doi: 10.1093/humrep/13.8.2321. [DOI] [PubMed] [Google Scholar]
  25. Grech V, Vassallo-Agius P, Savona-Ventura C. Secular trends in sex ratios at birth in North America and Europe over the second half of the 20th century. J Epidemiol Community Health. 2003;57:612–615. doi: 10.1136/jech.57.8.612. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Hertz-Picciotto I, Jusko TA, Willman EJ, Baker RJ, Keller JA, Teplin SW, et al. A cohort study of in utero polychlorinated biphenyl (PCB) exposures in relation to secondary sex ratio. Environ Health. 2008;7:37. doi: 10.1186/1476-069X-7-37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Jacobsen R, Møller H, Mouritsen A. Natural variation in the human sex ratio. Hum Reprod. 1999;14:3120–3125. doi: 10.1093/humrep/14.12.3120. [DOI] [PubMed] [Google Scholar]
  28. James WH. Evidence that mammalian sex ratios at birth are partially controlled by parental hormone levels around the time of conception. J Endocrinol. 2008a;198:3–15. doi: 10.1677/JOE-07-0446. [DOI] [PubMed] [Google Scholar]
  29. James WH. The variations of human sex ratio at birth with time of conception within the cycle, coital rate around the time of conception, duration of time taken to achieve conception, and duration of gestation: a synthesis. J Theor Biol. 2008b;255:199–204. doi: 10.1016/j.jtbi.2008.07.016. [DOI] [PubMed] [Google Scholar]
  30. James WH. Hypotheses on the stability and variation of human sex ratios at birth. J Theor Biol. 2012;310:183–186. doi: 10.1016/j.jtbi.2012.06.038. [DOI] [PubMed] [Google Scholar]
  31. James WH. Evolution and the variation of mammalian sex ratios at birth: reflections on Trivers and Willard (1973) J Theor Biol. 2013;334:141–148. doi: 10.1016/j.jtbi.2013.06.023. [DOI] [PubMed] [Google Scholar]
  32. Jarrell JF, Gocmen A, Akyol D, Brant R. Hexachlorobenzene exposure and the proportion of male births in Turkey 1935–1990. Reprod Toxicol. 2002;16:65–70. doi: 10.1016/s0890-6238(01)00196-4. [DOI] [PubMed] [Google Scholar]
  33. Jongbloet PH. Over-ripeness ovopathy: a challenging hypothesis for sex ratio modulation. Hum Reprod. 2004;19:769–774. doi: 10.1093/humrep/deh136. [DOI] [PubMed] [Google Scholar]
  34. Khanjani N, Sim MR. Reproductive outcomes of maternal contamination with cyclodiene insecticides, hexachlorobenzene and beta-benzene hexachloride. Sci Total Environ. 2006;368:557–564. doi: 10.1016/j.scitotenv.2006.03.029. [DOI] [PubMed] [Google Scholar]
  35. Kolk M, Schnettler S. Socioeconomic status and sex ratios at birth in Sweden: No evidence for a Trivers-Willard effect for a wide range of status indicators. Am J Hum Biol. 2016;28:67–73. doi: 10.1002/ajhb.22756. [DOI] [PubMed] [Google Scholar]
  36. Koshy G, Delpisheh A, Brabin L, Attia E, Brabin BJ. Parental smoking and increased likelihood of female births. Ann Hum Biol. 2010;37:789–800. doi: 10.3109/03014461003742803. [DOI] [PubMed] [Google Scholar]
  37. Martin JF. Length of the follicular phase, time of insemination, coital rate, and the sex of offspring. Hum Reprod. 1997;12:611–616. doi: 10.1093/humrep/12.3.611. [DOI] [PubMed] [Google Scholar]
  38. Martin SA, Jr, Harlow SD, Sowers MF, Longnecker MP, Garabrant D, Shore DL, et al. DDT metabolite and androgens in African-American farmers. Epidemiology. 2002;13:454–458. doi: 10.1097/00001648-200207000-00014. [DOI] [PubMed] [Google Scholar]
  39. Mathews TJ, Hamilton BE. Trend analysis of the sex ratio at birth in the United States. Nat Vital Stat Rep. 2005;53:1–17. [PubMed] [Google Scholar]
  40. McDonald E, Watterson A, Tyler AN, McArthur J, Scott EM. Multi-factorial influences on sex ratio: a spatio-temporal investigation of endocrine disruptor pollution and neighborhood stress. Int J Occup Environ Health. 2014;20:235–246. doi: 10.1179/2049396714Y.0000000073. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Mocarelli P, Brambilla P, Gerthoux PM, Patterson DG, Jr, Needham LL. Change in sex ratio with exposure to dioxin. Lancet. 1996;348:409. doi: 10.1016/s0140-6736(05)65030-1. [DOI] [PubMed] [Google Scholar]
  42. Mocarelli P, Gerthoux PM, Ferrari E, Patterson DG, Jr, Kieszak SM, Brambilla P, et al. Paternal concentrations of dioxin and sex ratio of offspring. Lancet. 2000;355:1858–1863. doi: 10.1016/S0140-6736(00)02290-X. [DOI] [PubMed] [Google Scholar]
  43. Mumford SL, Kim S, Chen Z, Gore-Langton RE, Boyd Barr D, Buck Louis GM. Persistent organic pollutants and semen quality: The LIFE Study. Chemosphere. 2015;135:427–435. doi: 10.1016/j.chemosphere.2014.11.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Nieminen P, Lehtiniemi H, Huusko A, Vähäkangas K, Rautio A. Polychlorinated biphenyls (PCBs) in relation to secondary sex ratio - a systematic review of published studies. Chemosphere. 2013;91:131–138. doi: 10.1016/j.chemosphere.2012.11.019. [DOI] [PubMed] [Google Scholar]
  45. Nicolopoulou-Stamati P, Pitsos MA. The impact of endocrine disrupters on the female reproductive system. Hum Reprod Update. 2001;7:323–330. doi: 10.1093/humupd/7.3.323. [DOI] [PubMed] [Google Scholar]
  46. Ober C. The maternal-fetal relationship in human pregnancy: an immunogenetic perspective. Exp Clin Immunogenet. 1992;9:1–14. [PubMed] [Google Scholar]
  47. Phillips DL, Pirkle JL, Burse VW, Bernert JT, Jr, Henderson LO, Needham LL. Chlorinated hydrocarbon levels in human serum: effects of fasting and feeding. Arch Environ Contam Toxicol. 1989;18:495–500. doi: 10.1007/BF01055015. [DOI] [PubMed] [Google Scholar]
  48. Pocar P, Brevini TA, Fischer B, Gandolfi F. The impact of endocrine disruptors on oocyte competence. Reproduction. 2003;125:313–325. doi: 10.1530/rep.0.1250313. [DOI] [PubMed] [Google Scholar]
  49. Potashnik G, Goldsmith J, Insler V. Dibromochloropropane induced reduction of the sex-ratio in man. Andrologia. 1984;16:213–218. doi: 10.1111/j.1439-0272.1984.tb00266.x. [DOI] [PubMed] [Google Scholar]
  50. Potashnik G, Porath A. Dibromochloropropane (DBCP): a 17-year reassessment of testicular function and reproductive performance. J Occup Environ Med. 1995;37:1287–1292. doi: 10.1097/00043764-199511000-00007. [DOI] [PubMed] [Google Scholar]
  51. Ralph JL, Orgebin-Crist MC, Lareyre JJ, Nelson CC. Disruption of androgen regulation in the prostate by the environmental contaminant hexachlorobenzene. Environ Health Perspect. 2003;111:461–466. doi: 10.1289/ehp.5919. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Richardson DB, Ciampi A. Effects of exposure measurement error when an exposure variable is constrained by a lower limit. Am J Epidemiol. 2003;157:355–363. doi: 10.1093/aje/kwf217. [DOI] [PubMed] [Google Scholar]
  53. Salazar-García F, Gallardo-Díaz E, Cerón-Mireles P, Loomis D, Borja-Aburto VH. Reproductive effects of occupational DDT exposure among male malaria control workers. Environ Health Perspect. 2004;112:542–547. doi: 10.1289/ehp.112-1241918. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Schisterman EF, Vexler A, Whitcomb BW, Liu A. The limitations due to exposure detection limits for regression models. Am J Epidemiol. 2006;163:374–383. doi: 10.1093/aje/kwj039. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Schrader TJ, Cooke GM. Examination of selected food additives and organochlorine food contaminants for androgenic activity in vitro. Toxicol Sci. 2000;53:278–288. doi: 10.1093/toxsci/53.2.278. [DOI] [PubMed] [Google Scholar]
  56. Sjödin A, Jones RS, Lapeza CR, Focant JF, McGahee EE, 3rd, Patterson DG., Jr Semiautomated high-throughput extraction and cleanup method for the measurement of polybrominated diphenyl ethers, polybrominated biphenyls, and polychlorinated biphenyls in human serum. Anal Chem. 2004;76:1921–1927. doi: 10.1021/ac030381+. [DOI] [PubMed] [Google Scholar]
  57. Skakkebaek NE, Rajpert-De Meyts E, Main KM. Testicular dysgenesis syndrome: an increasingly common developmental disorder with environmental aspects. Hum Reprod. 2001;16:972–978. doi: 10.1093/humrep/16.5.972. [DOI] [PubMed] [Google Scholar]
  58. Soto AM, Sonnenschein C, Chung KL, Fernandez MF, Olea N, Serrano FO. The E-SCREEN assay as a tool to identify estrogens: an update on estrogenic environmental pollutants. Environ Health Perspect. 1995;103:S113–S122. doi: 10.1289/ehp.95103s7113. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Taylor KC, Jackson LW, Lynch CD, Kostyniak PJ, Buck Louis GM. Preconception maternal polychlorinated biphenyl concentrations and the secondary sex ratio. Environ Res. 2007;103:99–105. doi: 10.1016/j.envres.2006.04.009. [DOI] [PubMed] [Google Scholar]
  60. Terrell ML, Berzen AK, Small CM, Cameron LL, Wirth JJ, Marcus M. A cohort study of the association between secondary sex ratio and parental exposure to polybrominated biphenyl (PBB) and polychlorinated biphenyl (PCB) Environ Health. 2009;8:35. doi: 10.1186/1476-069X-8-35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Terrell ML, Hartnett KP, Marcus M. Can environmental or occupational hazards alter the sex ratio at birth? A systematic review. Emerg Health Treats J. 2011;4:7109. doi: 10.3402/ehtj.v4i0.7109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Tiido T, Rignell-Hydbom A, Jönsson B, Giwercman YL, Rylander L, Hagmar L, et al. Exposure to persistent organochlorine pollutants associates with human sperm Y:X chromosome ratio. Hum Reprod. 2005;20:1903–1909. doi: 10.1093/humrep/deh855. [DOI] [PubMed] [Google Scholar]
  63. Toft G, Hagmar L, Giwercman A, Bonde JP. Epidemiological evidence on reproductive effects of persistent organochlorines in humans. Reprod Toxicol. 2004;19:5–26. doi: 10.1016/j.reprotox.2004.05.006. [DOI] [PubMed] [Google Scholar]
  64. Upson K, De Roos AJ, Thompson ML, Sathyanarayana S, Scholes D, Barr DB, et al. Organochlorine pesticides and risk of endometriosis: findings from a population-based case-control study. Environ Health Perspect. 2013;121:1319–1324. doi: 10.1289/ehp.1306648. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Vested A, Giwercman A, Bonde JP, Toft G. Persistent organic pollutants and male reproductive health. Asian J Androl. 2014;16:71–80. doi: 10.4103/1008-682X.122345. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Weinberg CR, Baird DD, Wilcox AJ. The sex of the baby may be related to the length of the follicular phase in the conception cycle. Hum Reprod. 1995;10:304–307. doi: 10.1093/oxfordjournals.humrep.a135932. [DOI] [PubMed] [Google Scholar]
  67. Weisskopf MG, Anderson HA, Hanrahan LP Great Lakes Consortium. Decreased sex ratio following maternal exposure to polychlorinated biphenyls from contaminated Great Lakes sport-caught fish: a retrospective cohort study. Environ Health. 2003;2:2. doi: 10.1186/1476-069X-2-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Zorn B, Sucur V, Stare J, Meden-Vrtovec H. Decline in sex ratio at birth after 10-day war in Slovenia: brief communication. Hum Reprod. 2002;17:3173–3177. doi: 10.1093/humrep/17.12.3173. [DOI] [PubMed] [Google Scholar]
  69. Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–706. doi: 10.1093/aje/kwh090. [DOI] [PubMed] [Google Scholar]

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