Using the Bayesian Cluster Profiling approach, our results suggest that social vulnerability characteristics tend to be on the extremes—i.e., with some areas having high domestic well use and low social vulnerability and other areas with high well use having high social vulnerability. In contrast, when assessing the number of houses with wells in a census tract with the social vulnerability index (comparison model), we find a simple inverse relationship with the index. The lower the amount of vulnerability (low SVI), the higher the number of wells per tract. This is not useful or helpful information as it fails to identify that certain locations served by private wells are more socially vulnerable than others and have different vulnerability profiles. Similar studies have also noted that the index is not always useful or helpful for evaluating environmental health-related inequities.22,48 Well ownership is spatially complex. The distinct vulnerability profiles that are related to domestic wells use have heterogenous measures of vulnerability as well as being spatially heterogeneous.
Certain cluster profiles were significantly more likely to lack access to public water supply. The cluster profile with the highest domestic well use was cluster 15 ([IRR = 5.17, (95%CI 1.66, 16.18, p < 0.01)]; range of estimated number of households using wells (mean = 274, 3rd quartile = 12, max = 3131l 7 tracts with more than 1,000 households estimated to be using private wells). This cluster was characterized by relatively low social vulnerability. In contrast, however, at least two clusters (12 and 14) with elevated risk for a lack of public water supply were characterized as having elevated social vulnerability. This result highlights the complex relationships that exist between public water supply access and social vulnerability; a relationship that is otherwise obscured when relying on the SVI.
Race/ Ethnicity & Poverty
It has been noted in other studies that a lack of access to safe drinking water in the United States is associated with race/ethnicity, as well as poverty. 49,50 In a study of environmental injustice regarding a population’s nearness to unconventional gas development in the state of Pennsylvania, Clough and Bell in 2016 found that race and ethnicity were not associated with proximity to unconventional gas development, but poverty was. 20
With regards to minority race and/or ethnicity, we found that the census tracts with the highest proportions of minority populations were more likely to have access to public water. This differs from what was found in Wake County, North Carolina when MacDonald Gibson et al. found a positive relationship between a population’s proportion of black persons and the odds of being excluding from a municipal water service. 18 In PA, it is not surprising that areas served by private wells, which are rural, have a lower proportion of black populations, given that during World War I, the “Great Migration” began with southern black populations settling predominately in urban centers of northern states, which in PA included Philadelphia and Pittsburg and other surrounding industrial cities such as Chester and Norristown. 51 This pattern of settlement of black population in the urban areas of PA differs from that of the settlement pattern in North Carolina, where black populations historically predominantly lived in the rural areas of the state. 52 We found no evidence that minority race and/or ethnicity was related to exclusion from public water supply in this analysis. It should be noted here that this analysis did not consider water insecurity or consider lack of access to public water supply due to inability to pay, either a water bill or the fee to hook up to a water supply. It also did not consider whether the water was clean or safe (e.g., lead contamination). 53,54 In the report, Closing the Water Access Gap in the US: A National Action Plan, Roller and Gasteyer et al. report that, “…race is the strongest predictor of water and sanitation access.” The analysis in Roller and Gasteyer was completed at the census tract level, but for the entire United States. Also, their definition of access was whether or not a household reported having complete plumbing using data from the 2010–2014 American Community survey, which asks if a home has, “hot and cold running water, a bathtub or shower, a sink with a faucet, or a flush toilet”. 50 This definition contrasts with the definition we have used, which is the area of census tract that falls within a public water supply service area. It is also acknowledged that a portion of the population is known to live within a public water supply area and still does not have public drinking water supplied to their homes.55,56
It may be that in Pennsylvania, the use of a private well (or lack of connection to a public water supply) may not be as strongly related to race as in other states. For clusters 10 through 14, we found that those residing in areas with a high density of domestic wells were more likely to own than rent their homes. People of color have experienced racial inequities when it comes to home ownership and therefore this may explain why race was not as strongly associated with private well density. 57 We found that census tracts in Pennsylvania that had the highest quartile of minority race/ethnicity also had the highest quartile of renters. These clusters of census tracts that have the largest proportion of racial and ethnic minority home renters were also least likely to have a domestic well, meaning, they were connected to publicly supplied water. However, it is important to note that having a connection to a public water supply, does not necessarily equate to access to a water supply, as those experiencing poverty can have their water shut-off. If this analysis was repeated with data on access to public water, including shut-off data, the cluster analysis may yield different results, particularly with respect to minority populations who can disproportionally lack access to water and sanitation services, even in high income countries like the US. 58
Housing Age, Age of Household Members, Education
Census tracts with younger median age of homes had larger amounts of domestic wells. All census tracts that were more likely to have domestic wells were either in the first or second quartile for median housing age, meaning that the housing was younger than the median age. This does not mean that the houses are new, because housing throughout the state of Pennsylvania is some of the oldest in the United States 59. Philadelphia and Allegheny counties, which are urban with no domestic wells, have houses with a median age of 73 and 64 years, while Chester and Monroe counties are some of the youngest in the state with median home ages of 39 and 36 respectively. 59
Out of the clusters, cluster 12 had the 4th quartile of proportion of their population with children under the age of 17 and 5 years old. Cluster 14 was in the third quartile for both age groups. Cluster 13 was in the fourth quartile for their population being over the age of 65 years old. One of the main concerns regarding exposure to domestic wells is exposure to pathogens. Gastroenteritis is the most common illness caused by pathogens found in domestic well water. Children under the age of 5 are highly susceptible to gastroenteritis, as well as those over the age of 65. 60,61
All the clusters that had high proportions of exposure to domestic wells fell in the second quartile for unemployment, except for cluster 14, which was in the third quartile. Cluster 14 was also in the fourth quartile for those who do not have a high school diploma.
In summary, we identified six different distinct census-tract cluster types that have increased risk of lacking access to public water, two of which also have high measures of social vulnerability. A census tract in Pennsylvania is most likely to have a large proportion of houses using domestic wells and also be experiencing social vulnerability if they are a population which, when compared to tracts in the rest of the state: own their home, has a large proportion of children under 17, has a median per capita income less than $30k per year, has a younger median age of homes, and has a higher proportion of those aged 25 or older that do not have a high school diploma or equivalent.
Strengths and Limitations
A major strength of this study is the use of publicly available data to understand area-specific context of social deprivation. Area-level deprivation is a well-validated approach that has been consistently associated with major infectious and chronic disease health outcomes48.
To our knowledge, this is the first study to use Bayesian profile regression to examine private domestic well use related to social vulnerability. This use of a flexible Bayesian clustering profile regression model is an efficient way to assess which social vulnerability attributes are related to private water supply ownership. The method enabled us to characterize areas in the state of Pennsylvania that are most likely to be served by non-PWS. The Bayesian profile regression was an appropriate choice to determine which covariates were clustering together. A weakness of this method is that it is less able to evaluate the independent effects of any single covariate as would be possible in conventional regression analysis. 62 Traditional multiple regression models can struggle with assessing an outcome when the exposures and covariates are related due to problems of collinearity. 39 Bayesian profile regression is appropriate for observing where patterns overlap, or rather, where certain conditions co-occur, while avoiding issues with collinearity. 35 The problems of lack of access to public water, as well as measures of social vulnerability, are interrelated making it difficult to tease out these relationships. The use of the clustering approach reduced the dimensionality of the measures to cope with the issue of collinearity. 39 Moreover, a clustering approach may be preferable compared to a simple index (e.g., SVI) since co-exposure patterns and their interrelationships may be complex and non-linear in a spatial sense 63.
Although the use of an ecologic study design is generally considered to be a weakness, here our research questions are all at the community level, because any potential interventions, would likely be at the community level. Another limitation is that we relied on the public water service boundary information and made assumptions regarding private well usage using these data. Our approach assumes that an area “not in the PWS area” is using domestic wells, and that the same proportion of area served by domestic wells is the same proportion as that of families in a census tract. Although this assumption is an imperfect proxy measure, it is the best data we had available. There are currently no complete registries of drinking water sources in PA for those using domestic wells. Although, some drilling records for wells are reported to the Pennsylvania Department of Conservation and Natural Resources, which are compiled and known as the PA Groundwater Information System 64, the drilling data are incomplete as they are not required to be reported in the state of PA, and the system has only been collecting these data since the 1970's. This means that using data only from this system would be an underestimation of the number of families using domestic wells, both in areas with wells completed before the 1970’s as well as wells completed in the 21st century. Another limitation of this work is that of temporal ambiguity. All we can assess is which factors co-occur, we cannot assess if social vulnerability leads to differences in public water infrastructure or if the opposite is true. 39
In the census tracts with only a proportion being served by public water supply, this estimate likely overestimates the number of households served by private wells, because the PWS areas are likely denser in population. This limitation is acknowledged, and we believe our approach is still the best estimate available for establishing the proportion of households served by private wells by census tract in the state of Pennsylvania.
Public Health Implications
Approximately 90% of the US is considered to have access to safely managed drinking water 17,49, which in the context of the US is deceiving, as this number includes those served by private, unregulated, untested and untreated domestic wells. If we were to say that only those served by public drinking water in US have access to safely managed drinking water, then this number would be drastically decreased. In the case of PA, an estimated 3 million of 12.79 million people are served by a private well, meaning only 76.5% have access to public drinking water.1,65
For the United States to achieve universal access to “safely managed water” to meet the United Nations Sustainable Development Goals, more progress needs to be made in addressing the gaps in access to safe drinking water, including providing support for homeowners served by a domestic well. Targeted interventions are needed to focus on these vulnerable, underserved populations and more research is needed to understand the social vulnerabilities of these populations so appropriate interventions can be developed. 58 These future interventions could include changes to domestic well installation rules, provision of free testing and treatment systems, the design of educational tools and campaigns, or developing a system for prioritizing which communities receive resources for public water infrastructure. The knowledge gained from our analysis in PA informs us that interventions and education campaigns need to be targeted towards homeowners (and some renters), and populations that are more socially vulnerable (have a low level of education, with an annual income less than $30k, are elderly or have children) as well as those that are less socially vulnerable (those with higher levels of education, an annual income over $30k, and are not a sensitive age). Interventions for these different groups would need to be conceived differently. For example, free testing programs could be made available for populations that are more vulnerable than those with more resources to afford water quality testing. Additionally, there are pockets of clusters 12 and 14 that appear on the outskirts of where public water supply ends. In these situations, these vulnerable populations could benefit from being hooked up to the public water supply. Although these populations would benefit from public water supply and wastewater, the reasons why connections are not extended can be very complex. One reason, and a major issue, is cost. Even if the community has the funding to extend water and wastewater services, the individual households which have never paid a monthly bill may be resistant to the change. The well water users may perceive their water as being safer and better than a public waters supply even though they likely do not have any facts by which to base these opinions. 66,67 Helping well water users understand the actual health risks, and the costs associated with maintaining a well water safety and an onsite wastewater system over the lifetime of a mortgage may help these populations make choices that are in their best interest.