The Impact of Bisphenol A and Triclosan on Immune Parameters in the U.S. Population, NHANES 2003–2006

Erin M. Rees Clayton; Megan Todd; Jennifer Beam Dowd; Allison E. Aiello

Environ Health Perspect. 2011;119(3):390-396.

Abstract and Introduction

Abstract

Background: Exposure to environmental toxicants is associated with numerous disease outcomes, many of which involve underlying immune and inflammatory dysfunction.
Objectives: To address the gap between environmental exposures and immune dysfunction, we investigated the association of two endocrine-disrupting compounds (EDCs) with markers of immune function.
Methods: Using data from the 2003–2006 National Health and Nutrition Examination Survey, we compared urinary bisphenol A (BPA) and triclosan levels with serum cytomegalovirus (CMV) antibody levels and diagnosis of allergies or hay fever in U.S. adults and children ≥ 6 years of age. We used multivariate ordinary least squares linear regression models to examine the association of BPA and triclosan with CMV antibody titers, and multivariate logistic regression models to investigate the association of these chemicals with allergy or hay fever diagnosis. Statistical models were stratified by age (< 18 years and ≥ 18 years).
Results: In analyses adjusted for age, sex, race, body mass index, creatinine levels, family income, and educational attainment, in the ≥ 18-year age group, higher urinary BPA levels were associated with higher CMV antibody titers (p < 0.001). In the < 18-year age group, lower levels of BPA were associated with higher CMV antibody titers (p < 0.05). However, triclosan, but not BPA, showed a positive association with allergy or hay fever diagnosis. In the < 18-year age group, higher levels of triclosan were associated with greater odds of having been diagnosed with allergies or hay fever (p < 0.01).
Conclusions: EDCs such as BPA and triclosan may negatively affect human immune function as measured by CMV antibody levels and allergy or hay fever diagnosis, respectively, with differential consequences based on age. Additional studies should be done to investigate these findings.

Introduction

Exposure to environmental toxicants is associated with numerous disease outcomes, many of which involve underlying immune and inflammatory dysfunction (Dietert et al. 2010). Mounting epidemiological evidence suggests that proper function of the immune system is a major determinant of health across the life course (Dietert et al. 2010). For example, those with childhood asthma may have an elevated risk of developing lung cancer (Dietert et al. 2010), and among individuals ≥ 87 years old, immune dysregulation has been linked with dementia (Katsel et al. 2009). Exposure to environmental toxicants, therefore, may cause life-long changes in response to infectious agents, in immune homeostasis, and in overall physical and mental health (Dietert et al. 2010).

One group of environmental toxicants affecting immune system function is endocrine-disrupting compounds (EDCs) (Chalubinski and Kowalski 2006). In 1996, the U.S. Congress first recognized EDCs as a public health concern when it mandated that the U.S. Environmental Protection Agency (EPA) develop a way to identify and monitor EDCs in the environment (Endocrine Society 2009). EDCs are substances found in food, personal care and other consumer products, pharmaceuticals, and the environment that have deleterious effects on human health, homeostasis, metabolism, and reproduction (Diamanti-Kandarakis et al. 2009). Synthetic EDCs form a diverse group of chemicals primarily used in pesticides, industrial chemicals, pharmaceuticals, and personal care products (Chalubinski and Kowalski 2006). Sources of exposure to EDCs can vary widely, ranging from occupational to in utero exposures (Barr et al. 2007). The stability (among other characteristics) of many EDCs that makes these substances beneficial for industry also means that high levels of these chemicals can be detected in water, air, and soil even years after being banned from use, which results in extended windows of time during which humans may be exposed (Diamanti-Kandarakis et al. 2009). Although the exact physiological mechanisms of action are unknown for many EDCs, they mimic or affect hormones (Diamanti-Kandarakis et al. 2009). Despite increasing research on the effects of EDCs on human health, controversy surrounds the issue of what concentrations—if any—of these chemicals are safe for human use.

The industrial chemical bisphenol A (BPA) is a prevalent EDC in human products and environments (Vandenberg et al. 2010; Welshons et al. 2006). BPA (4,4'-isopropylidenediphenol) is used primarily as a component of polycarbonate plastics, epoxy resins, and dental sealants, with > 800 million kg BPA produced each year in the United States alone (Diamanti-Kandarakis et al. 2009). Among the many health effects associated with BPA exposure, this chemical has been linked with abnormal male and female reproductive organ development in animals (Vandenberg et al. 2010) and sperm anomalies in humans (Meeker et al. 2010).

According to U.S. EPA guidelines, safe levels of BPA intake are 50 μg/kg body weight/day, assuming that the main source of exposure is from ingestion. In a recent analysis of 2005–2006 National Health and Nutrition Examination Survey (NHANES) data, the median daily intake of BPA in the United States was estimated to be 0.034 μg/kg/day, which is well below the U.S. EPA guidelines of 50 μg/kg/day (Lakind and Naiman 2010). Nevertheless, studies suggest that the U.S. EPA guidelines and the conclusion that current dietary intake levels are safe should be reevaluated (Vandenberg et al. 2010). First, low-dose exposures to BPA (> 200 times below the U.S. EPA recommended dose) in pregnant mice negatively affected mammary gland development of female offspring by increasing ductal area and extension, promoting fat pad maturation, and decreasing epithelial cell size (Vandenberg et al. 2007). In addition, tumor-promoting agonistic effects of BPA on a mutant androgen receptor in a human prostate adenocarcinoma cell line were more pronounced at low doses than at higher doses (Keri et al. 2007). Therefore, EDCs may possess nonlinear dose–response dynamics, with low doses causing greater abnormalities. Second, urinary BPA levels have not been shown to decline consistently with increasing fasting times; this finding suggests that dietary exposure may not be the only important source of exposure, or that BPA is not cleared rapidly from the body (Stahlhut et al. 2009; Vandenberg et al. 2010). Thus, a need exists to better understand how chronic exposure to low doses of BPA may affect human health.

Another prevalent EDC, triclosan (2,4,4'-trichloro-2'-hydroxydiphenyl ether), was first introduced in the 1960s for use in personal care products as an antimicrobial and preservative. Since then, triclosan has been added to countless consumer products, including, but not limited to, hand soaps, laundry detergents, toothpastes, wound disinfection solutions, deodorants, facial tissues, plastic kitchen utensils, medical devices, and toys [Centers for Disease Control and Prevention (CDC) 2010; U.S. EPA 2010]. The proliferation of triclosan as an "antibacterial" ingredient coincides with mounting evidence of its bioaccumulation and persistence in human fat tissue, umbilical cord blood, human breast milk, and urine (Smith and Lourie 2009). The most likely routes of exposure to triclosan are ingestion and absorption through the skin (Calafat et al. 2008). The CDC, in a study conducted from 2003 through 2004 among a representative sample of the U.S. general population ≥ 6 years of age, found triclosan at unadjusted concentrations of 2.4–3,790 μg/L in the urine of 75% of Americans (Calafat et al. 2008). The significance of this finding remains unknown.

Despite the initial safety data demonstrating triclosan's tolerance by humans, more recent studies have found that it may have detrimental effects on the central nervous system and may be linked to allergies and asthma (Glaser 2004; Kepner 2004–2005). Triclosan was first labeled as an EDC in 2006 when Veldhoen et al. (2006) demonstrated that triclosan (at concentrations as low as 0.15 μg/L) decreased body weight and accelerated thyroid hormone–mediated hind limb development in the bullfrog Rana catesbeiana. Thus, triclosan may not mimic thyroid hormones but may influence how they act, affecting the development and metabolism of not only frogs but all species that depend on thyroid hormone signaling, including humans.

The ability of chemicals such as BPA and triclosan to interfere with the endocrine system, and the interactions between the endocrine and immune systems, suggests that EDCs may also target immune function (Ahmed 2000; Chalubinski and Kowalski 2006). Immunological changes, including increased CD4⁺:CD8⁺ratios, decreased proliferation of peripheral blood mononuclear cells, and increased frequency of autoantibodies, have all been observed in humans with occupational exposures to pesticides containing EDCs (Ahmed 2000; McConnachie and Zahalsky 1992; Rosenberg et al. 1999; Straube et al. 1999). Yet, no epidemiological data have been examined to determine whether BPA or triclosan influences immune function. Natural estrogen (17β-estradiol) has been shown to disrupt morphology of the thymus and bone marrow, protect the main cells of the immune system (T, B, and antigen-presenting cells) from apoptosis, and regulate the synthesis of antibodies in the serum and female genital tract (Ahmed 2000; Donner et al. 1999; Grossman 1984; Verthelyi and Ahmed 1998; Wira and Sandoe 1987). It is therefore plausible that EDCs such as BPA and triclosan, which possess estrogenic activity (Ishibashi et al. 2004), may exert similar effects within the body.

Laboratory studies have also shown that EDCs, such as BPA, diethylhexyl phthalate, and 4-tert-octylphenol, can be involved in the development of allergies by increasing interleukin-4 production and IgE levels (Chalubinski and Kowalski 2006; Lee et al. 2003). For triclosan, some have hypothesized that using this antimicrobial ingredient may increase allergies among humans via the "hygiene hypothesis." The hygiene hypothesis, first proposed by Strachan (1989), has evolved into a potential explanation for the increase in allergic and autoimmune diseases observed in recent decades, particularly in developed countries. This hypothesis attributes the rise in allergies to the increase in clean, hygienic living environments and subsequent decrease in exposure to infectious agents (Okada et al. 2010). Exposure to triclosan and other antibacterial agents may lead to an excessively clean environment that disrupts the usual development of the immune system by eliminating or changing the commensal microbiota that normally help to shape the immune system (Levy 2001; Okada et al. 2010).

To begin to address the gaps that exist in understanding how environmental exposures and immune dysfunction are related, we investigated the association of two EDCs with markers of immune function. We hypothesized that exposure to BPA and triclosan may lead to impaired immune function and increased allergies. Using data from the 2003–2006 NHANES, we examined whether urinary levels of BPA and triclosan were associated with reported allergies or measured serum antibody titers to a common pathogen of the herpes virus family, cytomegalovirus (CMV). Increased CMV antibody titers are considered a marker of altered cell-mediated immune function (Dowd and Aiello 2009; Koch et al. 2006; McDade et al. 2000; Stowe et al. 2007), and high antibody levels indicate that the cellular arm of the immune response is less effective in keeping the virus in a persistent latent state (Roberts et al. 2010). CMV antibody levels are useful as a marker of immune function because primary infection with this virus often occurs at a very young age, the virus persists in the infected host for life, and containment of the virus becomes a top priority for the immune system (Dowd and Aiello 2009; Koch et al. 2006). This study provides an important first step toward understanding how two prevalent EDCs, BPA and triclosan, may interact with human immune function.

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Table 1. Estimated population means and frequencies for demographic characteristics of study population, NHANES 2003–2006.
Characteristic	Weighted mean or percentage (95% CI)	Linearized SE	n
Age (years)	35 (33.36–35.82)	0.60	3,728
Male (%)	50.5 (48–53)	1.10	3,728
BMI (kg/m²)	26.6 (26.13–27.05)	0.22	3,728
Lab measure
Triclosan (ng/mL)	116.3 (105.43–127.11)	5.31	3,728
BPA (ng/mL)	4.4 (4.07–4.82)	0.18	3,728
CMV seropositive (%)	46.7 (42–52)	2.40	1,496
CMV-antibody level (if seropositive)	2.1 (1.93–2.17)	0.06	805
Creatinine (mg/dL)	134.9 (130.27–139.61)	2.29	3,728
Ever diagnosed with allergies or hay fever (%)	33.8% (31–36)	1.10	2,232
Race (%)
Non-Hispanic white	68.3 (63.3–72.9)	2.40	1,457
Non-Hispanic black	12.9 (1–16.5)	1.60	1,073
Mexican American	9.7 (7.5–12.5)	1.20	933
Other race/ethnic groups	9.1 (7.4–0.11.1)	0.90	265
Family income [US$(2000)]	51,706 (48,809–54,603)	1,418	3,728
Family income quartile [US$(2000)]
1	8,985		894
2	25,108		1,153
3	47,005		736
4	96,102		945
Head of household educational attainment (%)
< High school	17.2 (15.3–19.2)	1.00	1,044
Completed high school	24.8 (22.6–0.27.2)	1.10	898
> High school	58.0 (54.8–61.2)	1.60	1,786

Table 2. Estimated mean triclosan and BPA levels, by sociodemographic characteristics, NHANES 2003-2006.
Characteristic	Triclosan		BPA
Characteristic	Mean (ng/mL)	p-Value	Mean (ng/mL)	p-Value
CMV		0.741		0.235
Seropositive	103.63		5.53
Seronegative	99.38		4.83
Ever diagnosed with allergies or hay fever		0.814		0.633
Yes	122.76		3.78
No	127.53		4.09
Sex		0.008		0.451
Male	136.76		4.58
Female	95.38		4.31
Race		0.095		< 0.001
Non-Hispanic white	110.56		4.04
Non-Hispanic black	110.74		5.38
Mexican American	160.59		5.32
Other race/ethnic groups	119.56		5.21
Family income quartile		0.119		0.001
1	94.80		5.73
2	103.94		4.61
3	113.41		4.37
4	138.06		3.75
Head of household educational attainment		0.608		0.629
< High school	121.01		4.51
Completed high school	103.55		4.69
> High school	120.31		4.32

Mean triclosan and BPA levels are weighted. p-Values are from a Wald test of the difference between these weighted means.

Table 3. Association between triclosan levels and immune function measured by CMV antibody levels, NHANES 2003–2004.
Independent variable	Model 1		Model 2
Independent variable	< 18 years of age (n = 252)	≥ 18 years of age (n = 368)	< 18 years of age (n = 252)	≥ 18 years of age (n = 368)
Ln(triclosan) (ng/mL)	0.003 (0.046)	−0.024 (0.031)	0.012 (0.046)	−0.022 (0.032)
Age (years)	−0.026 (0.014)	0.020 (0.004)***	−0.025 (0.015)	0.021 (0.004)***
Male	−0.093 (0.136)	−0.316 (0.074)***	−0.130 (0.127)	−0.311 (0.079)**
BMI (kg/m²)			0.005 (0.009)	−0.003 (0.008)
Creatinine (mg/dL)	0.001 (0.001)	0.001 (0.001)	0.001 (0.001)	0.000 (0.001)
Race
Non-Hispanic black	0.039 (0.101)	0.123 (0.097)	0.077 (0.147)	0.046 (0.111)
Mexican American	0.028 (0.146)	0.093 (0.114)	0.109 (0.209)	−0.045 (0.115)
Other race/ethnic groups	−0.092 (0.252)	−0.081 (0.168)	−0.003 (0.260)	−0.136 (0.183)
Family income quartile
2			−0.176 (0.150)	−0.109 (0.133)
3			−0.276 (0.215)	−0.122 (0.117)
4			−0.063 (0.207)	−0.353 (0.176)
Head of household education
Completed high school			0.193 (0.185)	−0.095 (0.147)
> High school			0.121 (0.163)	−0.096 (0.161)

Data are β-coefficients (SEs) for each independent variable in the regression models. Models are OLS regressions with CMV antibody level as the dependent variable, estimated among respondents with detected levels of triclosan. Only respondents < 50 years of age are included. Model 1 includes age, sex, creatinine, and race as covariates; model 2 includes all of these plus BMI, family income, and educational attainment.
**p < 0.01. ***p < 0.001.

Table 4. Association between BPA levels and immune function measured by CMV antibody levels, NHANES 2003–2004.
Independent variable	Model 1		Model 2
Independent variable	< 18 years of age (n = 335)	≥ 18 years of age (n = 452)	< 18 years of age (n = 335)	≥ 18 years of age (n = 452)
Ln(BPA) (ng/mL)	−0.104 (0.053)	0.186 (0.034)***	−0.113 (0.047)*	0.158 (0.035)***
Age (years)	−0.011 (0.013)	0.017 (0.004)***	−0.012 (0.012)	0.018 (0.004)***
Male	−0.151 (0.117)	−0.250 (0.078)**	−0.154 (0.109)	−0.239 (0.078)**
BMI (kg/m²)			0.004 (0.008)	0.001 (0.006)
Creatinine (mg/dL)	0.001 (0.001)*	−0.001 (0.001)	0.001 (0.001)*	−0.001 (0.001)
Race
Non-Hispanic black	0.179 (0.086)	0.158 (0.082)	0.145 (0.103)	0.095 (0.093)
Mexican American	0.105 (0.084)	0.128 (0.108)	0.090 (0.097)	−0.006 (0.115)
Other race/ethnic groups	0.288 (0.150)	−0.111 (0.141)	0.294 (0.154)	−0.211 (0.168)
Family income quartile
2			−0.275 (0.134)	−0.055 (0.101)
3			−0.275 (0.164)	−0.166 (0.099)
4			−0.107 (0.138)	−0.305 (0.132)*
Head of household education
Completed high school			0.070 (0.148)	−0.136 (0.108)
> High school			−0.015 (0.105)	−0.136 (0.154)

Data are β-coefficients (SEs) for each independent variable in the regression models. Models are OLS regressions with CMV antibody level as the dependent variable. The model is estimated among respondents with detected levels of BPA. Model 1 includes age, sex, creatinine, and race as covariates; model 2 includes all of these plus BMI, family income, and educational attainment.
*p < 0.05. **p < 0.01. ***p < 0.001.

Table 5. Association between triclosan levels and immune function measured by allergies or hay fever diagnosis: NHANES 2003–2006.
Independent variable	Model 1		Model 2
Independent variable	< 18 years of age (n = 678)	≥ 18 years of age (n = 766)	< 18 years of age (n = 678)	≥ 18 years of age (n = 766
Ln(triclosan) (ng/mL)	1.245 (0.109)*	1.004 (0.075)	1.257 (0.097)**	0.996 (0.074)
Age (years)	1.043 (0.029)	1.015 (0.008)	1.023 (0.029)	1.014 (0.009)
Male	1.396 (0.239)	0.624 (0.148)	1.379 (0.229)	0.631 (0.151)
BMI (kg/m²)			1.024 (0.019)	1.004 (0.014)
Creatinine (mg/dL)	0.999 (0.001)	0.999 (0.001)	0.999 (0.002)	0.999 (0.002)
Race
Non-Hispanic black	1.199 (0.313)	0.781 (0.201)	1.303 (0.354)	0.803 (0.223)
Mexican American	0.439 (0.135)*	0.578 (0.130)*	0.588 (0.190)	0.755 (0.202)
Other race/ethnic groups	1.202 (0.417)	0.807 (0.261)	1.226 (0.456)	0.880 (0.269)
Family income quartile
2			0.691 (0.334)	1.216 (0.349)
3			0.498 (0.146)*	0.801 (0.298)
4			0.760 (0.295)	1.099 (0.351)
Head of household education
Completed high school			2.488 (0.855)*	1.638 (0.568)
> High school			3.107 (1.209)*	2.198 (0.665)*

Data are ORs (SEs) for allergy or hay fever diagnosis among unit changes (or categories) of the independent variable. Models are logistic regressions with dependent variable ever diagnosed with allergies or hay fever, estimated among respondents with detected levels of triclosan. Only respondents < 50 years of age are included. Model 1 includes age, sex, creatinine, and race as covariates; model 2 includes all of these plus BMI, family income, and educational attainment.
*p < 0.05. **p < 0.01

Table 6. Association between BPA levels and immune function measured by allergies or hay fever diagnosis: NHANES 2003–2006.
Independent variable	Model 1		Model 2
Independent variable	< 18 years of age (n = 793)	≥ 18 years of age (n = 1,340)	< 18 years of age (n = 793)	≥ 18 years of age (n = 1,340)
Ln(BPA) (ng/mL)	0.910 (0.113)	0.896 (0.098)	0.933 (0.123)	0.903 (0.094)
Age (years)	1.045 (0.032)	1.001 (0.005)	1.029 (0.035)	1.003 (0.005)
Male	1.679 (0.262)**	0.707 (0.124)	1.632 (0.236)**	0.692 (0.123)
BMI (kg/m²)			1.023 (0.016)	1.006 (0.010)
Creatinine (mg/dL)	1.000 (0.002)	1.000 (0.001)	1.000 (0.002)	1.000 (0.001)
Race
Non-Hispanic black	1.085 (0.256)	0.718 (0.121)	1.167 (0.292)	0.778 (0.133)
Mexican American	0.415 (0.107)**	0.527 (0.100)**	0.541 (0.155)*	0.724 (0.167)
Other race/ethnic groups	1.247 (0.367)	0.728 (0.218)	1.286 (0.399)	0.815 (0.265)
Family income quartile
2			0.783 (0.344)	1.063 (0.230)
3			0.646 (0.169)	0.839 (0.248)
4			0.956 (0.331)	1.220 (0.265)
Head of household education
Completed high school			1.669 (0.689)	1.775 (0.438)*
> High school			2.109 (0.990)	2.312 (0.436)***

Data are ORs (SEs) for allergy or hay fever diagnosis among unit changes (or categories) of the independent variable. Models are logistic regressions with dependent variable ever diagnosed with allergies or hay fever. Model is estimated among respondents with detected levels of BPA. Model 1 includes age, gender, creatinine, and race as covariates; model 2 includes all of these plus BMI, family income, and educational attainment.
*p < 0.05. **p < 0.01. ***p < 0.001.

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