A Structural Equation Model to Decipher Relationships among Water, Sanitation, and Health in Colonias-Type Unincorporated Communities

Abstract

The colonias along the United StatesMexico border are generally self-built neighborhoods of low-income families that lack basic infrastructure. While some government assistance has provided roads and electricity, water and wastewater services are still lacking in many colonias. This research is the first to collect a comprehensive dataset on water, sanitation, health, and living conditions in these unincorporated neighborhoods through collection of water samples and surveys; 114 households in 23 colonias across three geographically diverse Texas counties are studied. Water quality is assessed via traditional microbial indicators, chlorine, and arsenic. This complex dataset requires an advanced statistical tool to disentangle relationships among diverse factors. Structural equation modeling is utilized to identify relationships among surveyed and measured variables. The model reveals that colonias residents with well/hauled water accurately predict their water quality, while those with treated+piped water tend to think that their water is worse than it actually is. Dwelling quality and connection to sanitary sewers influence perceived health risks and household health, respectively. Furthermore, these communities have an overwhelming need and desire for point-of-use water treatment. This model can inform decision making and may be adapted to probe other questions and social dynamics for water and sanitation in unincorporated communities elsewhere.

Health impacts of water and sanitation insecurity in the Global North: a scoping literature review for U.S. colonias on the Mexico border

“…Most studies either focused on one or the other, with some studies only examining measured water quality using quantitative methodologies, and other studies only discussing perceived water quality using more qualitative methodologies (e.g., Moya 2017). However, Rowles et al (2020a) found that the relationships between perceived and measured water quality suggest that assessments of health and water quality should include measured data and not rely solely on resident perceptions. As differences in education level, resource wealth, and social capital vary from resident to resident, individual perceptions should be considered alongside quantitative data that can support or contrast those perceptions.…”

“…Nine of the included studies focused on water quality (Leach et al 1999(Leach et al , 2000Laware & Rifai 2006;Rios & Meyer 2009;Cardenas et al 2010;Travis et al 2010;Balazs et al 2011;Moore et al 2011;Rowles et al 2020b). Four studies examined environmental health (Berry et al 1997;Mier et al 2008;Moya 2017;Rowles et al 2020a), and three studies focused on mental health of water and sanitation insecurity (Garcia et al 2016;Hargrove et al 2018;Pierce et al 2019).…”

“…Specifically, distress surrounding water quality and pollution was related to concerns about the groundwater quality of wells (Berry et al 1997;Mier et al 2008). Rowles et al (2020a) discovered that decreased satisfaction with the dwelling environment corresponded with increased perceived health risk from current living conditions in TX colonias across three counties. This demonstrates that living conditions determined by the residents' their physical environment have a significant impact on the residents' distress water and sanitation-related.…”

“…Leading tools currently utilized to evaluate water insecurity such as the Water Poverty Index do little to capture resident perceptions on health and water quality, which have clearly been shown to influence health decision-making and mental health status (Korc & Ford 2013). On the other hand, tools that capture both quantitative health and water standards while considering resident perceptions can advise where there is a need for educational or infrastructure-related interventions in communities (Rowles et al 2020a). Thus, the development of tools and metrics to address health holistically as it pertains to water and sanitation comprises an innovative field of research.…”

Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

“…Some methods have been devoted to studying the interaction among accident factors, including System eoretic Accident Modeling and Processes (STAMP) [11,12], Functional Resonance Analysis Method (FRAM) [13], "2-4" model [14], Structural Equation Modeling (SEM) [15,16], etc. STAMP, FRAM, and the "2-4" model require finding out the interaction.…”