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Unregulated drinking water contaminants and adverse birth outcomes in Virginia [1]

['Holly A. Young', 'Department Of Geography', 'Virginia Tech', 'Blacksburg', 'Virginia', 'United States Of America', 'Korine N. Kolivras', 'Leigh-Anne H. Krometis', 'Department Of Biological Systems Engineering', 'Cristina E. Marcillo']

Date: 2024-06 

Abstract Through the Unregulated Contaminant Monitoring Rule (UCMR), the Environmental Protection Agency monitors selected unregulated drinking water contaminants of potential concern. While contaminants listed in the UCMR are monitored, they do not have associated health-based standards, so no action is required following detection. Given evolving understanding of incidence and the lack of numeric standards, previous examinations of health implications of drinking water generally only assess impacts of regulated contaminants. Little research has examined associations between unregulated contaminants and fetal health. This study individually assesses whether drinking water contaminants monitored under UCMR 2 and, with a separate analysis, UCMR 3, which occurred during the monitoring years 2008–2010 and 2013–2015 respectively, are associated with fetal health outcomes, including low birth weight (LBW), term-low birth weight (tLBW), and preterm birth (PTB) in Virginia. Singleton births (n = 435,449) that occurred in Virginia during UCMR 2 and UCMR 3 were assigned to corresponding estimated water service areas (n = 435,449). Contaminant occurrence data were acquired from the National Contaminant Occurrence Database, with exposure defined at the estimated service area level to limit exposure misclassification. Logistic regression models for each birth outcome assessed potential associations with unregulated drinking water contaminants. Within UCMR 2, N-Nitroso-dimethylamine was positively associated with PTB (OR = 1.08; 95% CI: 1.02, 1.14, P = 0.01). Molybdenum (OR = 0.92; 95% CI: 0.87, 0.97, P = 0.0) and vanadium (OR = 0.96; 95% CI: 0.92, 1.00, P = 0.04), monitored under UCMR 3, were negatively associated with LBW. Molybdenum was also negatively associated (OR = 0.90; 95% CI: 0.82, 0.99, P = 0.03) with tLBW, though chlorodifluoromethane (HCFC-22) was positively associated (OR 1.18; 95% CI: 1.01, 1.37, P = 0.03) with tLBW. These findings indicate that unregulated drinking water contaminants may pose risks to fetal health and demonstrate the potential to link existing health data with monitoring data when considering drinking water regulatory determinations at the national scale.

Citation: Young HA, Kolivras KN, Krometis L-AH, Marcillo CE, Gohlke JM (2024) Unregulated drinking water contaminants and adverse birth outcomes in Virginia. PLOS Water 3(5): e0000208. https://doi.org/10.1371/journal.pwat.0000208 Editor: Venkatramanan Senapathi, National College (Autonomous), VIET NAM Received: October 24, 2023; Accepted: April 1, 2024; Published: May 1, 2024 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Data Availability: Occurrence data from the Unregulated Contaminant Monitoring Rule are publicly available on the Environmental Protection Agency's website (https://www.epa.gov/dwucmr/occurrence-data-unregulated-contaminant-monitoring-rule) Individual-level birth records are restricted by each agency's Institutional Review Board (IRB) and cannot be made accessible to the public or research community. Contact information for the VDH IRB can be found here: https://www.vdh.virginia.gov/institutional-review-board/. Birth records are available from the Virginia Department of Health. Contact information for the VDH Vital Events Statistics Program can be found here: https://www.vdh.virginia.gov/vital-event-statistics-program/. Funding: This work was supported by the National Institute of Environmental Health Sciences (R21ES028396). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors declare the following financial interests/professional relationships which may be considered as potential competing interests: - Julia Gohlke reports financial support was provided by National Institute of Environmental Health Sciences. - Holly Young reports a relationship with United States Environmental Protection Agency that includes: employment.

Introduction Through the Safe Drinking Water Act (SDWA), the Environmental Protection Agency (EPA) regulates over 90 drinking water contaminants that may pose a risk to human health. These contaminants have health and/or technology-based National Primary Drinking Water Standards (i.e., Maximum Contaminant Levels, or MCLs) and are associated with known adverse effects following exposure. However, it is important to recognize that National Primary Drinking Water Standards do not encompass all potential waterborne exposures potentially associated with adverse human health outcomes. Contaminants may remain unregulated, even when suspected of downstream human health or environmental impacts, because they are typically present at very low (trace) levels, are specific to limited geographic areas, and/or because existing toxicological data are limited. Under the Unregulated Contaminant Monitoring Rule (UCMR), the EPA monitors occurrence of no more than 30 contaminants selected from the Drinking Water Contaminant Candidate List (CCL). These data are then used to justify existing or develop new regulatory standards [1]. Previous research linking the incidence of municipal drinking water contaminants with human health impacts is primarily limited to examining the impacts of regulated contaminants [2–5]. However, considerable emerging research suggests that contaminants currently listed on the CCL are directly associated with health outcomes [6–8] and/or their presence exacerbates the negative impacts of contaminants currently regulated under the SDWA [9]. At present there is considerable concern regarding issues of water affordability in the United States [10], and it is critical to recognize that the cost of regulating new contaminants can be quite high (e.g., >$1B for Orange County, CA to regulate PFAS alone) [11]. The establishment of new MCL standards and accompanying investment in new infrastructure and treatment technology must be justified via demonstration of potential reductions in burden of disease, however, no previous studies have examined connections between unregulated drinking water contaminants and fetal health. Given the potential long-term health implications and costs associated with adverse birth outcomes [12–14], infants are a critical population to explicitly examine when considering the implications of developing National Drinking Water Primary Standards for currently unregulated contaminants. Considering the previously stated basic and applied research needs, this effort examines the following research questions: Does an association exist between unregulated drinking water contaminants listed under UCMR 2 and/or UCMR 3 and birth outcomes within service areas in Virginia?

If there is an association between unregulated drinking water contaminants and birth outcomes, where do these contaminants occur in Virginia? The first research question regarding the presence of an association between unregulated drinking water contaminants and birth outcomes is addressed through logistic regression to determine whether these contaminants are associated with birth outcomes, specifically pre-term birth (PTB), low birth weight (LBW), and term low birth weight (tLBW). The second research question regarding where contaminants occur in Virginia is explored through an examination of the spatial occurrence of contaminants. Outcomes provide insight into potential connections between fetal health and unregulated drinking water contaminants as well as common incidence of these contaminants in Virginia, which should assist both researchers and regulators in prioritizing future monitoring efforts. Beyond the state of Virginia, which here serves as an ideal case study location due to both health outcome and water service area data availability, this study provides a framework for application in additional geographic regions and should spur the design of targeted studies in regions where local hydrogeology and land use render the detection of these UCMR contaminants more likely.

Background A brief overview of the evolution of National Primary Drinking Water Regulations and the Unregulated Contaminant Monitoring Rule Prior to the 1970s, nationwide studies revealed that water systems had been struggling with inadequate facilities, poor operating procedures, and uneven management of public water supplies in communities of all sizes, leading to extensive water quality problems across the country [15,16]. The Safe Drinking Water Act (SDWA), passed in 1974, gave EPA authority to regulate drinking water contaminants and delegate enforcement and implementation of regulations to states, territories, and tribes. Major amendments to the SDWA occurred in 1986 and 1996 to ensure access to safe drinking water to protect public health. Through their statutory authority, under the SDWA, EPA sets national drinking water standards by determining whether three main conditions are met: “(1) The contaminant may have an adverse effect on human health, (2) The contaminant is known to occur or there is substantial likelihood that the contaminant will occur in public water systems with a frequency and at levels of public health concern, (3) in the sole judgement of the Administrator, regulation of the contaminant presents a meaningful opportunity for health risk reduction for persons served by PWS” [17]. Once a National Public Drinking Water Regulation (NPDWR) is in effect, enforcement and implementation of the regulation is primarily the responsibility of states [16]. The EPA evaluates the Contaminant Candidate List (CCL), a list of contaminants that are unregulated but may warrant regulation by EPA and are known or expected to occur at public water systems, and other priority contaminants every five years to determine which contaminants should be monitored under the UCMR based off a multi-step prioritization [18]. UCMR occurrence data is used to advise future regulatory standards. All public water systems (PWSs) serving 10,000 or more people are required to monitor under the UCMR; for PWSs serving less than 10,000 people, 800 representative PWSs, including tribal water systems, are chosen to monitor [19]. UCMR 2 monitored contaminants from 2008 to 2010. Of the contaminants monitored are two insecticides, five flame retardants, three explosives, three parent acetanilides, six acetanilide degradants, and six nitrosamines [20] (Fig 1). UCMR 3 monitored contaminants from 2013 to 2015. Of the contaminants monitored are seven volatile organic compounds, one synthetic organic compound, six metals, one oxyhalide anion, six per fluorinated compounds, seven hormones, and two viruses [21] (Fig 1). PPT PowerPoint slide

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TIFF original image Download: Fig 1. Contaminants monitored under UCMR 2 and UCMR 3 categorized by contaminant type. https://doi.org/10.1371/journal.pwat.0000208.g001 Since the SDWA’s inception, there have been over 90 NPDWRs established through the SDWA and the overall drinking water quality in the United States has improved [17] as evidenced by decreases in infectious waterborne outbreaks [22]. However, the nation still faces challenges to ensure safe drinking water for all. Community water systems across the country are often under-resourced and lack adequate funding. Previous research suggests that these overburdened water systems may incur monitoring and reporting violations to avoid health-based violations that are often accompanied by stricter penalties such as requiring expensive treatment techniques [23]. While many community water systems are stuck in the cycle of not having the resources or funding to comply with NPDWRs and then faced with costly penalties they cannot afford, a general distrust of drinking water has grown in the United States. Reliance on bottled water has increased since the Flint, Michigan water crisis [24], most notably among Black and Hispanic populations [25]. Rebuilding trust requires more direct examinations of potential health effects and home water quality that can both identify associations of concern that require interventions and provide consumer peace of mind when identify the absence of adverse health outcomes. Contaminants of interest This section will review the human and/or fetal health impacts of unregulated drinking water contaminants that were identified in a water system service area in Virginia that monitored under UCMR 2 or 3 (Table 1). Only one contaminant, N-Nitroso-dimethylamine (NDMA), was identified in samples collected under UCMR 2, and 11 contaminants were identified in samples collected under UCMR 3. PPT PowerPoint slide

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TIFF original image Download: Table 1. Summary of literature reviewed for each contaminant and their corresponding minimum reporting level (MRL) under the UCMR. https://doi.org/10.1371/journal.pwat.0000208.t001

Data and methods UCMR data Data for UCMR 2 and 3 were acquired from the EPA’s National Contaminant Occurrence Database (NCOD) [45]. Downloaded data included: PWS ID and name, PWS type, counties and cities served, contaminant name, and sample collection date. As water system service area boundaries for Virginia are not publicly available [46], estimated service areas (n = 662) used in previous work by Marcillo et al. (2021) [47] and Young et al. (2023) [5] were applied. In brief, the approach developed by Marcillo et al (2021) [47] assigned populations to community water systems (CWSs) based on population served and proximity to the system (Fig 2). To determine proximity to CWS, the closest zip codes to a CWS were assigned to a corresponding water system until the population served by that system was fully assigned. It is important to recognize that water service areas do not always develop according to population proximity and can be driven by local socio-economic factors and politics [48], so these service areas should be viewed as an approximation. However, it is also worth noting that most counties in Virginia comprise multiple separately managed community water systems which can vary in service and quality. Therefore, the use of estimated service area boundaries, as opposed to county boundaries, enables a finer scale examination that potentially limits exposure misclassification. Only CWSs that had estimated service area data available and that sampled under UCMR 2 and 3 were considered for the analysis. UCMR 2 and UCMR 3 were analyzed separately; a total of 336 CWSs sampled under UCMR 2 and 346 CWSs sampled under UCMR 3 (Fig 2). PPT PowerPoint slide

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TIFF original image Download: Fig 2. This study includes 346 CWSs, represented as service areas, that sampled under UCMR 2 and UCMR 3. https://doi.org/10.1371/journal.pwat.0000208.g002 Birth outcome data Virginia birth records (n = 567,342) for the years covered by the UCMR 2 (2008, 2009, 2010) and the UMCR 3 (2013, 2014, and 2015) were acquired from the Virginia Department of Health (VDH) and accessed for research purposes from 23, February 2020 to 1, August 2021. During analysis, authors had access to information that could identify individual participants (e.g., mother’s address) stored on a secure university computer; the Virginia Department of Health IRB waived the requirement for individual informed consent for use of birth records. All analyses were performed according to protocols to protect confidentiality as approved by both Virginia Tech IRB (VT IRB #17–1190) and the Virginia Department of Health IRB (VDH IRB #40221). Birth record data included: mother’s self-reported information (including race, education, age, Hispanic origin, tobacco use, parity, and address) child information collected at birth (sex, gestational length, weight, plurality) and payment method (private insurance, Medicaid, self-pay). Data processing Monitoring frequencies can vary across systems depending on their size and source water type, and contaminant type [49]. Given the variation in monitoring frequency, analysis was conducted on an annual basis. Exposure period was classified via majority gestational year (MGY). Birth records were assigned to the year in which the majority of gestation occurred using gestational age and birth date to determine the midpoint of the gestational period [50,51]. For example, a birth that occurs in February would be matched with contaminant occurrence data in the previous year when most exposure during pregnancy would have occurred, rather than the year in which the birth occurred. Three outcomes of interest were calculated based on data acquired from the birth records: low birth weight (LBW) = <2500 grams, preterm birth (PTB) = <37 weeks of pregnancy, and term low birth weight (tLBW) = <2500 grams and >37 weeks of pregnancy [52,53], with each outcome classified as a binary variable (i.e. present/absent). The study was limited to singleton births, with all plural births removed due to their increased risk of preterm birth and low birth weight [54]. Birth records with any of the following were removed from the study: P.O box address, unknown birth weight, unknown gestational age, and incomplete address (Fig 3), resulting in a final sample size of 435,449 births. Esri’s 2013 StreetMap dataset was used to geocode birth records. PPT PowerPoint slide

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TIFF original image Download: Fig 3. Data processing for individual birth records in Virginia. Note birth records were geocoded to an estimated service area boundary that sampled under UCMR 2 and UCMR 3 (n = 346). https://doi.org/10.1371/journal.pwat.0000208.g003 Contaminant occurrence was aggregated at the estimated service area level for each year and binarily classified into [x] contaminant was not identified at a level above or equal to the MRL (0) or [x] contaminant was identified one or more times at a level above or equal to the MRL (1), where [x] contaminant represents one unregulated drinking water contaminant. Birth records were then joined to corresponding service areas for analysis. Contaminants that did not occur at one of the 346 estimated service areas in Virginia that were sampled under UCMR 2 and 3 were not considered. Statistical analyses Logistic regression models were built (or used) to determine if a relationship exists between unregulated drinking water contaminants and adverse birth outcomes within service areas in Virginia. Each birth outcome (PTB, LBW, and tLBW) was examined separately with each individual contaminant. Odds ratios and 95% confidence intervals (CI) were calculated to understand the relationship between the outcome of interest and unregulated contaminants. The following covariates were entered into the regression model: water system service area; majority gestational year; infant’s sex; parity/birth order; mother’s race, age, and education; if mother is of Hispanic origin; tobacco use during pregnancy (yes/no); and payment method. All analyses were completed using JMP statistical software.

Discussion Information on the health impacts, including adverse birth outcomes, associated with unregulated drinking water contaminants is limited (Table 1). In this association study, mothers who lived in a service area that had at least one occurrence of NDMA during the year in which the majority of gestation occurred were 8% (95% CI: 1.02–1.14) more likely to experience a PTB than mothers who did not live in a service area where NDMA occurred during the majority gestation year. The EPA has not required monitoring of NDMA since UCMR 2, and thus more recent occurrence data is limited. Future research is needed to examine the potential health impacts of this probable human carcinogen. Similarly, mothers who live in a service area where HCFC-22 was detected during the year in which the majority of gestation occurred were 18% (95% CI: 1.01–1.37) more likely to experience a tLBW than mothers who lived in a service area with no HCFC-22 occurrence during the majority gestation year. Animal studies examining inhalation of HCFC-22 in rats observed that exposed female rats had a statistically significant increase in liver, adrenal, pituitary, and kidney weights [55]. Palmer et al. (1978) [56] found that pregnant rats exposed to higher concentrations of HCFC-22 than the control group had lower fetal weight and increased fetal abnormalities. No past studies have examined the relationship between maternal ingestion of HCFC-22 and health outcomes, indicating a need for future research. It is important to note that while both HCFC-22 and NDMA are associated with industrial processes, NDMA is also a byproduct of disinfection processes which can vary between community water systems. In contrast to these solely anthropogenic contaminants, both molybdenum and vanadium enter water as a result of local geology and mineral content (e.g., erosion and weathering of the local landscape). Interestingly, both contaminants were associated with reductions, though quite small, in specific birth outcomes. For example, LBW was reduced by 8% (95% CI: 0.87–0.97) and the risk of a tLBW was reduced by 10% (95% CI: 0.82–0.99) for mothers living in service areas when molybdenum was above the MRL during the year in which the majority of gestation occurred. Research on the toxicity of molybdenum is limited, and even less is known on its potential to harm a fetus. It is worth noting that pregnant women require more dietary molybdenum than other adults [38]. Similarly, LBW is reduced by 4% (95% CI: 0.92–1.00) for mothers who lived in a service area where vanadium was detected above the minimum reporting level during the year when the majority of gestation occurred. Research examining the health impacts of vanadium on humans is inconclusive [43], with some studies suggesting that exposure to vanadium in low concentration can be therapeutic [44]. Naturally occurring geogenic contaminants have been associated with protective health impacts previously; for example, Kessing et al. (2017) [57] and Memon et al. (2021) [7] reported lowered risk for dementia and suicide, respectively, in populations exposed to higher levels of lithium in drinking water. Together these results support the need for more focused research on potential health benefits associated with waterborne ingestion of these metals by sensitive populations such as gestating mothers. Limitations and future research Assumptions were necessary to conduct this cross-sectional study. As mentioned previously, service areas were approximated [47] in order to refine exposure classification at a finer than county scale. The absence of publicly available service area data is recognized as a limitation in examinations of potential trends in community water exposures [46]. In addition, this work pre-supposes that mothers are consuming the water supplied to their homes, though recent work suggests that the consumption of bottled water and/or consumer treatment of home water prior to consumption is increasing, particularly in minority communities [25]. The detection of significant relationships despite these limiting assumptions is notable. Addresses of birth records were geocoded, presenting locational error at the individual level. As opposed to addresses in a city, there is often a higher geocoding error when locating addresses in a rural area. Although 88% of Virginia’s population lives in an urban area [58], it is worth noting that there is evidence of elevated incidence of adverse birth outcomes in rural areas [59]. Additional limitations of this study include assignment of births to majority gestational year, available covariates, and binomial classification of contaminants. Given that contaminant occurrence was aggregated yearly, majority gestational year (MGY) was estimated to define the exposure period. Contaminants were analyzed with birth records that corresponded to the MGY. Results of the study could be skewed if the infant was exposed during the minority gestational year (e.g., exposed in December and born in July). Future research could benefit from examining drinking water contaminants quarterly, rather than annually, particularly in areas with high adverse birth outcome incidence. It is worth noting that during the study period, race was recorded differently on original birth records. Prior to 2013, child’s race was used in lieu of mother’s race as mother’s race was not recorded on birth records until 2013. Additionally, ethnicity was reported as whether a mother was of Hispanic origin or not. Combinations of reported ethnicity and race were not considered, nor were races other than Black, white, or the combined category of other self-reported races due to low numbers in individual categories. Finally, since individual statistical tests were completed for each contaminant, the possibility of spurious associations is increased. The EPA requires all PWSs serving over 10,000 people and a subset of 800 PWSs serving less than 10,000 people to monitor for contaminants under the UCMR [18]. This study only considered contaminant info for water systems that were required to monitor under UCMR 2 and UCMR 3. Since monitoring frequency varies by water system size, contaminant occurrence was represented as binomial variables (yes = the contaminant occurred at least once at or above the MRL; no = the contaminant did not occur at or above the MRL). Future studies could benefit from looking at contaminant concentration and frequency of occurrence. As two of the contaminants with positively significant associations, molybdenum and vanadium, are geogenic in origin, it is important to recognize that the trends presented here with regard to contaminant occurrence are not necessarily generalizable to other states or regions with dissimilar hydrogeology; application of the demonstrated research framework, in particular in examining relations observed in Virginia, is highly recommended. Furthermore, these results suggest the need for further evaluation to determine if there is a potential risk for adverse birth outcomes when unregulated drinking water contaminants occur, especially considering frequency of occurrence at a finer spatial scale, which would allow the researcher to determine if additional drinking water regulations should be implemented locally.

Conclusion Our results indicate that NDMA and HCFC-22 may be associated with increased risk for adverse birth outcomes, suggesting the need for further research to determine if unregulated drinking water contaminants may pose a potential risk to fetal health. Additionally, some contaminants, such as molybdenum, may decrease the risk for adverse birth outcomes. Currently, a contaminant is only considered for regulation if it occurs at a frequency and at a level of public health concern nationally, and if it is a threat to public health based on available data. However, given that contaminants can occur frequently or at high levels locally, state-level examinations may assist in fine-tuning recommendations to ensure optimal health impacts. This research demonstrates that current unregulated drinking water contaminants may impact fetal health, and that more research on contaminant occurrence should be conducted to unravel remaining complexities related to water consumption, diet, and geolocation impacts.

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