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Re-Examination of Quality of Life Indicators in US - Mexico Border Cities: a Critical Review

  • Craig Allen TalmageEmail author
  • David Pijawka
  • Bjoern Hagen
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Abstract

This paper explores quality of life (QoL) in the US–Mexico Border region by revisiting The Border Observatory Project (BOP). The BOP collected and analyzed survey-response data derived from four pairs of border sister cities (Mexicali, Baja and Calexico, California; San Luis Rio Colorado, Sonora and San Luis/Somerton, Arizona; Juarez, Chihuahua and El Paso, Texas; Tijuana, Baja and San Diego, California) over time. This paper adds to the literature on QoL by identifying the social and QoL indicators particularly pertinent to U.S.–Mexico border cities and significant differences between cities. The BOP and recent literature on U.S.-Mexico border QoL and social indicators are described and leveraged to propose a border-rooted bi-national, multi-community, and multi-indicator social indicators framework for use in future QoL and social indicator studies regarding border cities. The commentary and proposed framework in this paper help inform future research, policy, and practice concerning residents and migrants found in border communities.

Keywords

U.S.-Mexico border Quality of life Happiness Border City disparities 

Background and Purpose

There is asymmetry in quality of life (QoL) along and across border communities (Pijawka et al. 2012; Sohn 2014; Wilder et al. 2013). Quality of life is not felt the same, is not observed the same, and does not occur in necessarily the same prevalence within or across border communities. Institutional, political, economic, and cultural differences and changes over time contribute to imbalance in and diversity of experience. Urban areas like those along the U.S.-Mexico border are susceptible to fluctuation and instability (McAslan et al. 2013; Pijawka et al. 2012), especially when significant economic, political, and social asymmetries exist. Furthermore, the U.S.-Mexico border remains complex because of the multinational global organizations, embedded traditional communities, and migrant passages and visitors found in border areas, which have existed before and after walls and continue to shift due to changes in immigration, asylum, and trade policies.

While quality of life has been explored on a macro-level across countries, even those that share borders, by excellent organizations such as OECD, community-level quality of life approaches are needed to understand the special nuances border regions experience. The U.S.–Mexico border region is a dynamic and unique case to explore substantial differences in QoL, because of subjective and objective divisions in sovereignty, nationality, and economic status, but not necessarily due to strong divisions in culture, despite physical barriers such as border checkpoints and walls. In communities like Nogales, Arizona and Nogales, Sonora, residents and leaders on both sides see themselves living in one community separated by a wall (Talmage 2012, see also Herzog and Sohn 2017 regarding Tijuana-San Diego). Still, U.S.-Mexican border communities can demonstrate disparities even among individuals and communities that share cultural, racial, ethnic, and/or familial backgrounds (Ruiz-Beltran and Kamau 2001). Again, some differences between border communities result from multinational and transnational industries that have eroded many cities’ distinct cultural and environmental ecologies (Peña 1997).

This manuscript revisits data collected from The Border Observatory Project (BOP): The State of the U.S.–Mexico Border Cities (Guhathakurta et al. 2010) and showcases other research and technical reports concerning QoL indicators on the U.S.-Mexico border (e.g. Talmage 2012). First, commentary is given regarding findings from QoL studies, weighing heavily on the BOP to inform future data collection practice on the U.S.-Mexico Border. The limitations of the BOP data and previous U.S.-Mexico border studies are discussed. Further analysis on the aggregate BOP data is also conducted to highlight essential indicators to be included in a new proposed bi-national social indicators framework. More specifically, this manuscript discusses: (1) the BOP indicators of QoL and differences between them for U.S. and Mexican cities’ and others’ research concerning those indicators and (2) proposes future indicators that should be included in a bi-national framework for future QoL and social indicator assessments in and across border cities.

Quality of Life Indicators

QoL is an output indicator of impact (positive or negative) on and/or perceived by individuals and communities, such that evidence-based policy or practice interventions be developed and implemented (Collins 2013). Concepts such as QoL, sustainability, urban living, and community development have intertwined in the literature. Examples of research on the intersection between these indicators are found in social indicators and urban-focused journals (e.g., Milbrath 1982; Sung and Phillips 2018; Talmage et al. 2018b). The QoL concept has roots in the ideas of sustainable and mutually beneficial human-environment relationships in that it integrates human physical and social structures (Dempsey et al. 2011; Hagen et al. 2017). Today, QoL, as a concept, is complex and multifaceted, which provides an alternative for communities and policy-makers who have traditionally only looked to economic indicators to describe their community well-being (Sirgy 2018; Sung and Phillips 2018).

QoL is also related to livability, which can also indicate the attractiveness of a community as a place to life, work, and leisure (Lee and Kim 2018). Livability is not only determined by economic vitality but also by culture and entertainment available to community members (Lee and Kim 2018). QoL is also linked to social justice and equity (Agyeman 2005; Barton 2000a; Burton 2000; Harvey 2010; Fainstein 2010). These concepts acknowledge the need for fair resource allocation and inclusiveness as well as full and equal access to all aspects of society (Dempsey et al. 2012).

Accessibility to local amenities is important to QoL and related to livability (Barton 2000a; Burton 2000). For instance, well-planned urban environments can reduce travel distances, provide transportation choices, and improve walkability, allowing all income classes to access to economic opportunities and local amenities (Hamiduddin 2015). These important amenities include facilities for education and employment training, decent housing, public services, social infrastructure, green spaces, and cultural and recreational services (Dempsey et al. 2011). Winter and Farthing (1997) identify eight services and facilities that have a significant positive impact. These include food shops, newsstands, open spaces, post offices, bars, supermarkets, primary and secondary schools. Additional research adds to this list by emphasizing the need for residents to have local access to doctors, restaurants and cafes, banks, and a community center (Aldous 1992; Burton 2000; Barton 2000b). In particular, access to schools is important, because schools can provide additional recreation spaces and serve as hubs for residents to learn and grow (Pstross et al. 2014; Talmage et al. 2018a).

Not all amenities are directly linked to the built environment; however, some are more abstract or intangible, such as decent housing and social infrastructure. A comprehensive literature study by Dempsey et al. (2011) and work by Hagen et al. (2017) identify vital non-physical and physical factors that contribute to socially sustainable communities and overall high QoL (Table 1). These indicators can be useful for future bi-national border indicator studies. While all of the indicators listed in Table 1 cannot be realistically encompassed in a single study, the BOP offers an important starting point for discussing the indicators data necessary to explore QoL across and along the U.S.-Mexico border.
Table 1

List of non-physical and physical QoL indicators

Non-physical factors

Predominantly physical factors

• Education, training, and cultural traditions

• Urbanity

• Social-justice, −inclusion, −capital, −order, −cohesion, −networks, and -interaction

• Attractive public realm

• Neighborhood

• Participation, local democracy, and active community organization

• Decent housing

• Walkability

• Health, quality of life, and well-being

• Local environmental quality and amenity

• Sense of community, cohesion, and belonging

• Accessibility

• Safety, employment, residential stability, mixed tenure, fair distribution of income

• Sustainable urban design

Adapted from Dempsey et al. (2011) and Hagen et al. (2017)

Revisiting the Border Observatory Project

Few studies have specifically analyzed bi-national QoL data using both qualitative and quantitative methods (e.g., McAslan et al., 2013; Pijawka et al. 2012). The Border Observatory Project: The State of the U.S.–Mexico Border Cities (Guhathakurta et al. 2010), hereafter called the BOP, appears to be one of the only readily accessible archives of both quantitative and subjective QoL indicators for the U.S.-Mexico border region. For the original project, researchers collected empirical indicators from 2004 to 2010 for four sister city pairs (eight cities total)— Mexicali, Baja California and Calexico, California; San Luis Rio Colorado, Sonora and San Luis/Somerton, Arizona; Juarez, Chihuahua and El Paso, Texas; and, Tijuana, Baja California and San Diego, California. Over 3800 individuals from eight cities: Mexicali, Baja (n = 302); Calexico, California (n = 98); San Luis Rio Colorado, Sonora (n = 398); San Luis – Somerton, Arizona (n = 347); Juarez, Chihuahua (n = 417); El Paso, Texas (n = 196); Tijuana, Baja (n = 1079); and, San Diego, California (n = 1007) participated in BOP research. In sum, 2196 households were in Mexico and 1648 were in the U.S.

The BOP researchers gathered responses via door-to-door household surveys across each of the eight border communities. Participants responded to questions concerning perceptions involving nine categories. These nine categories, shown with descriptions in Table 2, serve as indicators of QoL and livability. These factors include: (1) QoL and community satisfaction; (2) emotional well-being; (3) environmental quality; (4) education; (5) safety; (6) housing; (7) accessibility and transportation; and (8) public services. Two of the categories served as general QoL indicators (Table 2). Seven served as indicators of livability indicators (Table 2). The indicators reflected the descriptions found in Table 2. As also seen in Table 2, emotional well-being included indicators such as happiness, life satisfaction, enjoyment of daily activities, and feelings of elation or complete happiness.
Table 2

List of QoL and livability (L) indicators

Category

Description

QoL and Community Satisfaction (QoL)

Personal ratings of QoL, satisfaction with the city, perceiving the city as a good place to raise children, and the friendliness of the residents

Emotional Well-Being (QoL)

Positive or negative well-being, such as happiness, life satisfaction, enjoyment of daily activities, and feelings of elation or complete happiness

Environment (L)

Perceived air quality and health concerns, perceived quality of piped water and health concerns, and the quality of parks and recreation in their city

Education (L)

Quality of schools for children, and colleges and universities

Economic (L)

Perceptions regarding change in economic situation and cost of living since the previous year and how they perceive their situation in the coming year

Public Safety (L)

Perceptions of crime, safely walking alone after dark, and trust in local police

Housing (L)

Housing satisfaction, the proportion of individuals who rent or own their homes, and whether housing costs impose a financial burden

Transportation (L)

Number of cars per household, traffic congestion, commuting, and quality of public transportation

Public Services (L)

Perceived quality of trash collection services, street lighting, fire department services, roads, and the responsiveness of their local government

In the BOP, a Likert-scale-based survey instrument was used in annual surveys of the four pairs of sister cities. Each set of livability and QoL indicators (Table 2) had at least ten questions derived from the literature. BOP researchers asked respondents to rate the indicators on a one-to-nine Likert scale with “one” representing the lowest negative perceptions and “nine” representing the highest positive perceptions. The survey instrument was designed to ensure matches in wording between the Spanish and English versions and piloted before full implementation.

Various universities have used the BOP data to measure various relationships around QoL indicators with other explanatory factors including new approaches to happiness research. Yet, the BOP has not been followed by longitudinal, comprehensive, or multi-city studies on social indicators of quality of life, nor has a framework for future bi-national QoL studies been put forward to reexamine the unique and complex dynamics of QoL across and between cities along the U.S.-Mexico border. The BOP does address changes over four years for the Calexico and Mexicali communities (see Guhathakurta et al. 2010); however, longitudinal changes need more exploration, because they highlight whether some indicators may be more fragile or malleable than others in the system.

This manuscript provides a unique contribution to the BOP’s initial work in the late 2000s by revisiting the BOP’s approach, investigating significant aggregate level differences in the BOP, and proposing structures for future bi-national border research. The work presented in this paper specifically showcases and comments on the BOP’s subjective indicators of QoL data. The original BOP findings are not reproduced in this manuscript, but they receive comment and critique from the paper authors based on current border challenges and the limitations of the BOP in order to build a bi-national social indicators framework for future investigation.

Aggregate Level Significant Differences in Indicators

While not the most rigorous approach, t-tests were run on aggregate secondary subjective indicator data from the BOP. This cursory investigation helps point to important indicators to include in a later presented investigative framework for bi-national social indicators Table 3 outlines the results of t-test comparisons.
Table 3

Significant differences between U.S. and Mexico Cities (n = 8) on social factors

Category

Indicator

U.S.

Mexico

Statistic

Public Safety

Walking Alone After Dark

6.720

4.525

t(6) = 4.484, p ≤ .01, r2 = .770

Trust in Local Police

6.823

4.345

t(3.289*) = 4.089, p ≤ .05, r2 = .836

Housing

Housing Satisfaction

7.800

7.402

t(6) = 2.336, p ≤ .10, r2 = .476

Environment

Air Quality

6.385

5.028

t(6) = 2.862, p ≤ .05, r2 = .577

Transportation

Number of Cars Per Household

2.030

1.545

t(6) = 4.239, p ≤ .01, r2 = .750

Number of Cars Per Person

0.577

0.347

t(6) = 3.378, p ≤ .05, r2 = .655

Public Services

Fire Department Services

7.895

7.395

t(6) = 2.633, p ≤ .05, r2 = .536

Quality of Roads

6.630

5.123

t(6) = 5.403, p ≤ .01, r2 = .830

*Degrees of freedom decreased because the homogeneity of variance assumption was violated

Mexican residents appear to report lower livability than their U.S. counterparts. Specifically, Mexican residents demonstrate significant but only slightly lower levels related to feeling safe walking alone in their neighborhoods after dark, housing satisfaction, and road quality than U.S. respondents. Additionally, levels of trust in their local police and perceived levels of fire department services and air quality were much lower. Also, the mean number of cars per person and the mean number of cars per household were lower in Mexico than in the U.S, which can serve as a proxy for economic security and economic well-being. Recognizing that discrepancies and disparities exist between countries and across cities, a bi-national framework for assessing quality of life across U.S.-Mexico border communities is needed. But, what would such a robust bi-national framework concern?

Towards Building a Bi-National Framework for Assessing Quality of Life in the U.S.–Mexico Border Region

The lack of a bi-national framework and follow up research to the BOP is unfortunate, especially today as the U.S.-Mexico border and border security along that border have become strong topics of debate in U.S. and Mexican policy and practice. Mexico and the United States share a 1954-mile (3145-km) border. The border line covers four U.S. states and six Mexican states with 48 legal border crossing points, and is at the center of much political and public dialogue regarding drug smuggling, human trafficking, international trade, and migration (i.e., illegal, legal, and asylum seeking). For example, the 45th U.S. President Donald Trump partially shutdown the U.S. federal government in winter 2018–2019 to attempt to gain funding for the construction of a multibillion dollar wall along the U.S.-Mexico border, and he also considered declaring a national state of emergency to exercise emergency powers to override the Congress of the United States to secure such funding (Shepard 2019; Sonmez and Wagner 2019). Furthermore, the American public appears to blame the president for the 2018–2019 partial government shutdown, the longest in U.S. history, and they also slightly oppose border wall construction more than they support construction (Shepard 2019). Moreover, Mexico, especially its president Enrique Pena Nieto, also does not support wall construction nor do they want to share the cost to pay for it (González 2017). Even further, the deaths of migrants (often not from Mexico) crossing the border and migrant children being held in border detention facilities have raised alarm in both U.S. and Mexico that border and immigration policy and practice need to change, which will likely impact QoL and social life in border communities (Barbaro 2019; Montoya-Galvez 2018). Finally, life on the border has been described as a humanitarian crisis, specifically the lives of migrants crossing or attempting to cross the border (Barbaro 2019; Peña et al. 2017; Soler and Beatrice 2018). In particular, drug smuggling and human trafficking across the border can go hand-in-hand (Sanchez 2018).

Safety Concerns

Illegal immigration can easily be construed as more of a U.S. concern, as Mexicans and other Central/South Americans seek work or refuge in the U.S. However, undocumented persons reside and work on both sides of the border. Many individuals conduct trade across their respective borders to earn their incomes, some legally, others illegally. For instance, individuals can attain a SENTRI border-crossing card that allows them to travel more easily between the U.S. and Mexico. These passes are not work visas, but individuals will sometimes use them to gain entry for employment (Chávez 2011). In fact, visa overstays in the U.S. are estimated to outnumber crossings by undocumented persons (Warren and Kerwin 2017). More recently, the typical illegal border crossers have shifted from Mexican males seeking work to often include non-Mexican families seeking asylum (Barbaro 2019).

While illegal immigration is not assessed in the BOP, it affects QoL in border communities in both positive and negative ways. The BOP used the QoL indicator ‘safety’ to subjectively determine if people feel safe, a factor influencing QoL and satisfaction/livability. Despite perceptions to the contrary, crime rate statistics for U.S. border cities generally show that they are safer areas on average than other cities in their states (Gomez et al. 2011). Yet, regional violence has been linked to psychological trauma and the erosion of social bonds and trust among border communities, thereby impacting perceptions of safety and QoL (Slack et al. 2016). Furthermore, researchers have demonstrated links between individuals’ immigration status and health-related QoL (Garcini et al. 2018).

The BOP showcased greater public safety concerns on the Mexican side of the border compared to the U.S., which is consistent with previous research (e.g., Coronado and Orrenius 2007). Fire department services and quality of roads, which fall under municipal control, are perceived as worse in Mexico than the U.S. consistent with the BOP’s work. Sosa (2008) noted that public services continue to be a planning challenge in the region. Wildfires are common in the region because of drought and high temperatures. Fire departments help communities decrease wildfire risks by conducting prescribed burns, which also impact air quality (Henderson et al. 2005).

Environmental Concerns

In addition to immigration, researchers have posited links between climate change and human migration. Climate change has and will have human migration effects. Along the U.S.-Mexico border, these effects are associated primarily with the reduction in crop yields (Feng et al. 2010). The region’s semi-arid environment has also seen agricultural intensification, making it particularly vulnerable to climate changes. Climate change has already negatively impacted water quality and quantity along the U.S.-Mexico border (Duran-Encalada et al. 2017). Climate change and its effects will impact the livelihoods of rural individuals, jeopardizing their access to resources (Wilder et al. 2010). The 1994 North American Free Trade Agreement (NAFTA) compounded these issues; it spurred rapid urbanization and industrialization, raising additional concerns regarding climate impacts on water availability and quality (Hargrove et al. 2018; Norman et al. 2012; Vela et al. 2018; Wilder et al. 2010).

NAFTA also gave rise to maquiladoras, “foreign-owned industries using imported raw materials” (Carter et al. 1996, p. 590). Maquiladoras have brought concerns regarding air quality, water quality, and hazardous waste to the forefront. While social movements and NGOs have worked to address these concerns (Liverman et al. 1999), little data is available for informed policy decisions (Carter et al. 1996; Liverman et al. 1999). As a result, calls have gone out for accessible information and collective action (Varady et al. 2013). Furthermore, scientists have expressed grave concerns regarding the construction and environmental effects of President Trump’s proposed border wall (Bolstad 2017). These are similar environmental concerns to those expressed regarding the passed Secure Fence Act of 2006 under President George W. Bush (Lasky et al. 2011).

Poor environmental conditions in the region are connected to poor physical and mental health especially in the colonias, which are informal, unregulated periphery urban subdivisions (Hilfinger Messias et al. 2017; Marquez-Velarde et al. 2015; Mier et al. 2008; O'Connor et al. 2008). The term, colonia, means neighborhood or community in Spanish (Hilfinger Messias et al. 2017). Texas’ Office of the Secretary of State (2017) defines “a ‘colonia’ as a residential area along the Texas-Mexico border that may lack some of the most basic living necessities, such as potable water and sewer systems, electricity, paved roads, and safe and sanitary housing.” Colonias’ residents also tend to have particular struggles with property rights and structural issues with their homes (Sullivan and Olmedo 2015). In the BOP, San Luis - Somerton, AZ subjectively reported the lowest quality levels of potable piped water (Guhathakurta et al. 2010).

Air quality has become a growing concern regarding disparities across the border (Anderson and Gerber 2008). In the BOP, U.S. residents owned more cars per capita than Mexican persons, which is consistent with the U.S. being known as an auto-centric country compared to other countries (e.g., Statista.com 2014; Talmage and Frederick 2019). Yet in the BOP, Mexican residents perceive their air quality to be worse than their U.S. counterparts. According to the Western Sustainability and Pollution Prevention Network (WSPPN 2017), this is in large part due to power plants and industrial facilities, agricultural operations, mining, dust from unpaved roads, open burning of trash, and the regulatory differences of the two countries regarding these activities as well as vehicle emissions. In the BOP, Ciudad Juarez, El Paso, San Diego, and Tijuana (in that order) were noted to have the worst perceived health risks regarding local air quality (Guhathakurta et al. 2010). While not directly researched in the BOP or generally in border communities, autobuses have not been known for their fuel efficiency and optimal emissions; thus, many researchers and practitioners have looked at alternative-fuels and energy sources to decrease emissions and improve air quality (Tzeng et al. 2005). The types vehicles and fuels used across border cities in relationship to QoL needs to be further investigated, as exposure to transportation-generated particulate matter can have negative health effects as well as issues with road quality facets (Chan et al. 2002).

The NAFTA was recently updated and (debatably) replaced by the United States-Mexico-Canada Agreement (USMCA). The USMCA outlines increases in the number of truck and car parts made in North America, and it also immediately and gradually increases the wage requirement for some workers in car manufacturing facilities in all three countries. The wage increase particularly impacts Mexican manufacturers with generally lower wage workers compared to the U.S. and Canada. The USMCA substantially upgrades labor and environmental regulations, which impact safety regulations and unionization. These again have special impacts on Mexico, which has been lighter on regulations and harsher on unions (Long 2018). Notably, USMCA appears to not require any assessment of its impact on community health and QoL in and across border communities, which gives merits to and impetus for future independent research investigations of its effects and impact.

Health Factors

Health concerns and investigations have been broadly conducted across the border region and border cities (e.g., Borges et al. 2016; Cherpitel et al. 2015), but across-city and across-country indicator comparisons have not been often or longitudinally made. Health has become a greater border concern as many U.S. residents come to Mexico to attain alcohol and drugs (Cherpitel et al. 2015). Pulmonary issues such as asthma and allergies have been investigated in El Paso regarding indoor residential environments (Svendsen et al. 2018). Similar investigations regarding hazardous air pollutants have also occurred in Hildago County, Texas (Carrillo et al. 2018). Also in El Paso, researchers have investigated the sexual risk of HIV transmission (Kutner et al. 2017) and physical activity among border residents (Vasquez et al. 2018). Type 2 Diabetes has also arisen as a particularly prevalent health concern for those living California and Mexico (Barquera et al. 2018; Rosales et al. 2017). Others have investigated gastrointestinal issues such as irritable bowel syndrome among residents on both sides of the border (Molokwu et al. 2017; Zuckerman et al. 2018). The health of sex workers and sexual violence (in general) in the region has also been investigated (Nowotny et al. 2017; Semple et al. 2017). Finally, homelessness has also been researched (Moya et al. 2017).

Individual Capacity

From the BOP, individual capacity (i.e., community, economic, and social capacity) appears already present across border cities, and it must not be overlooked and should be accounted for when looking to improve such capacity. Individual capital or capacity has large and important connections to social capital or capacity (e.g., Kapucu 2011), which was not explicitly investigated in the BOP. Jones (2015) noted that households who have at least one migrant living abroad see their economic situations as more improved than households not in that situation, yet these households appear to have lower levels of social cohesion and happiness overall. Additionally, the quality of life of elders living in border cities has become a topic of interest. Single and married older adults appeared to demonstrate higher levels of quality of life on the border compared to widowed or divorced older adults (Gutiérrez-Vega et al. 2018).

Happiness and Satisfaction

Studies from the BOP data show that QoL and happiness indicators are generally similar and good across border cities despite country location (e.g., Collins and Ley García 2014; Guhathakurta et al. 2010). U.S. and Mexican individuals and communities may not view community assets, QoL, or individual well-being factors like happiness differently than their other-country counterparts despite real differences in objective indicators. Several scholars have speculated on reasons for comparatively high urban QoL and community satisfaction metrics in the border regions (Pijawka et al. 2012), but greater research and comparisons are needed on livability factors like those explored by the BOP (e.g., education, public safety, and public services). Also, comparisons of satisfaction and well-being indicators amongst U.S.-Mexico border studies are not readily found in the literature outside of the BOP.

Notable Trends in Border Concerns

Safety and environmental concerns have dominated high-level, policy-level, and societal discussions related to QoL. This dominating narrative highlights the large opportunity for social indicators researchers to inform future research, policy, and practice regarding border communities, especially U.S.-Mexico border communities. While environmental concerns have been investigated regarding housing (e.g., O'Connor et al. 2008), industry (Liverman et al. 1999), and border barriers (e.g., Bolstad 2017; Lasky et al. 2011), little discussion and research has occurred that can inform sustainable practices across border communities outside of the BOP. Issues such as poor health, food insecurity, low education, high unemployment, and social capital remain and must be addressed to unearth reasons for variations in health and QoL in specific areas (e.g., Collins 2013; Weigel and Armijos 2018).

Positing a bi-National Social and QoL Indicators Framework for Investigation

Future bi-national social and QoL indicators studies must take theory-based, complex, comprehensive, and multifaceted approaches (Sung and Phillips 2018; Sirgy 2018). Sirgy (2018) notes that indicators should not only include output or outcome indicators but input or action indicators as well. Individual-level, local community-level, and regional-level indicators of well-being should also be assessed (Sirgy 2018; Sung and Phillips 2018). Sirgy (2018) highlights that indicators showcase not only when communities and individuals are doing well (i.e., well-being), but also when they are doing poorly (i.e., ill-being). Given the special challenges experienced by individuals and communities on both sides of the border, this notion is essential to be included in a bi-national framework. Sirgy (2018) also notes that indicators must be able to compare vulnerable segments of communities to the community at large. Finally, indicators must be understood in the various contexts that they are applied, such as reaching particular goals or undertaking particular policy or community development interventions (Sung and Phillips 2018).

First, they can investigate quality of life and social indicators on the individual border city level. These investigations should make sure to include and compare both cities on each side of the border. For example, Mayor Arturo Garino of Nogales, Arizona states, “I consider Nogales: Nogales, a city divided by a fence” (Talmage 2012, p. 3). Studies like these have been discussed in this paper, but rarely do these studies cover more one or two pairs of U.S.-Mexico border cities or multiple sets of social and QoL indicators. Often, these studies have focused on safety, environmental, and health concerns, but not all three together. Again, few studies have examined happiness and satisfaction among other subjective indicators.

Second, studies can take multi-region approaches comparing border regions in multiple border areas such as Arizona-Sonora or Texas-Chihuahua. QoL and social indicator investigations comparing different regions can inform policy and practice to improve urban and border conditions. Again, these studies are most beneficial when they address multiple indicators. These investigations are sorely needed given the current geo-political climate. Policy discourse in the public media takes broad strokes when comparing U.S. and Mexico, but border city comparisons of high research quality could provide for more informed and substantial discussions of how to improve QoL on both sides of the border. Moreover, if such comparisons were made longitudinally, policy-makers could measure the impacts of and make adjustments to their interventions over time.

Third, longitudinal approaches are needed to understand changes over time, such as changes in policy and practice regarding social indicators and QoL indicators. The BOP project did complete a short-term, multi-year comparison, but longer investigations are needed to better understand shifts in QoL and life on the U.S.-Mexico border. These multi-year comparisons, especially involving cities on both sides of the U.S.-Mexico border, will be difficult given the resources needed to support such research endeavors. Funding needs to be cultivated for such longitudinal endeavors.

Fourth, studies of QoL in border regions should also explore the health of migrants living on both sides of the U.S.-Mexico border (Handley and Sudhinaraset 2017). Handley and Sudhinaraset (2017) conducted a literature review of fifty-nine studies regarding migrant health on both sides of the border. They write, “In future work it will be important to focus on developing interventions that can address migration-exacerbated health disparities and that are responsive to local and national policy contexts that affect health and healthcare that migrants encounter” (p. 115). To achieve their aims, future researchers will need bi-national, multi-community, and multi-indicator frameworks to investigate social and QoL indicators. Finally, immigration status, if possible, needs to be included among such investigations because of its demonstrated connection to QoL (Garcini et al. 2018).

Bejarano and Shepherd (2018) propose a border-rooted paradigm for post-secondary education; this manuscript offers a border-rooted bi-national, multi-community, and multi-indicator social indicators framework for community well-being research (see Tables 4 and 5). This framework can serve as a foundation or starting point for researchers looking to ascertain funding for large-scale studies, but also can serve as a guide for those looking to start with one smaller-scale study that can potentially be expanded in the future. If possible, matched sampling and matched comparisons should be conducted in addition to repeated-measures strategies in future border indicators studies. Table 4 contains the matching information needed in addition to repeated-measures needed.
Table 4

Information needed for matched sampling and repeated measures strategies

Person

Country comparison

Immigration status

City/county

Date/period of measurement

Mexican (MX) Resident

U.S. Resident and/or U.S./Mexican Migrant

Yes (When), No (In Process or Not in Process)

Name of U.S./MX City/County

Date One, Date Two, …, Date (__)

U.S. Resident

Mexican Resident and/or U.S./Mexican Migrant

Yes (When), No (In Process or Not in Process)

Name of U.S./MX City/County

Date One, Date Two, …, Date (__)

Migrant (in Mexico)

U.S. Migrant and/or U.S./Mexican Resident

Yes (When), No (In Process or Not in Process)

Name of U.S./MX City/County

Date One, Date Two, …, Date (__)

Migrant (in U.S.)

Mexican Migrant and/or U.S./Mexican Resident

Yes (When), No (In Process or Not in Process)

Name of U.S./MX City/County

Date One, Date Two, …, Date (__)

Table 5

Revised and proposed list of subjective QoL and social (S) indicators

Category

Description

Community Well-Being (QoL)

• Perceptions of community QoL

• Satisfaction with the city

• Perceiving the city as a good place to raise children

• Perceived friendliness of community members

• Perceived quality of culture-specific resources

Individual and Emotional Well-Being (QoL)

• Perceptions of individual QoL

• Happiness

• Life satisfaction

• Enjoyment of daily activities

• Feelings of elation or complete happiness

• Individual efficacy and capacity

Health Related Quality of Life (QoL)

• Current or previous substance abuse/use

• Food security and nutrition behaviors

• Perceived overall health

• Perceived changes in overall health

• Perceived future health (i.e., health outlook)

• Perceived quality of health care providers

• Physical activity levels

• Reported chronic health conditions

Environment (S)

• Perceived air quality*

• Health concerns regarding air quality

• Perceived quality of piped water

• Health concerns regarding water

• Quality of available natural resources

• Access to and quality of parks and recreation

Education (S)

• Quality of early childhood education centers

• Quality of elementary and secondary schools

• Quality of post-secondary schools (e.g., colleges and universities)

• Access to school facilities and resources

Economic (S)

• Current income level and employment status

• Perceived economic situation

• Perceived change in economic situation

• Perceived previous economic situation

• Perceived future economic situation (i.e., economic outlook)

Public Safety (S)

• Concerns regarding migration and immigration

• Perceptions of crime and violence

• Perceptions of local police (e.g., trust in local police*)

• Safety concerns (e.g., walking alone after dark,* high summer heat, and fire safety)

Housing (S)

• Housing satisfaction*

• Perceived housing quality

• Rent/own Home

• Burden of housing costs (e.g., rent/mortgage payments and utility payments)

Public Services (S)

• Perceived quality of trash collection services

• Perceived quality of street lighting

• Perceived quality of roads*

• Perceived quality of fire department services*

• Perceived responsiveness of local government and other local institutions

Transportation (S)

• Number of cars per person* and per household*

• Perceived traffic congestion

• Commuting behavior

• Quality of public transportation

Social (S)

• Individuation and self-expression

• Protests and elite-challenging action

• Sense of community, social cohesion, and social support

• Collective efficacy and community empowerment

• Neighboring behavior

• Citizen/community participation

• Perceptions of community and political leaders

• Perceptions of for-profit and nonprofit institutions and leaders

• Neighborhood tenure

• Access to community spaces

*Denotes indicator significantly differed on the aggregate country-level in BOP study

Table 5 contains the indicators that are especially pertinent to QoL and social indicators studies concerning residents and migrants living and moving through the U.S.-Mexico border. These indicators are largely derived from the BOP, but complemented by other indicators found in the literature. The largest additions are health-related quality of life and the social category. The social category is derived from frameworks for community well-being and psychological social capital (e.g., Perkins et al. 2002; Talmage et al. 2017; Welzel et al. 2005). While helpful, this is not an all-encompassing list of possible indicators for future use. Table 5 also denotes indicators worthy of more attention, because of significant differences found in the BOP data.

Overcoming the Limitations of the Border Observatory Project

While the BOP had robust sample sizes in the Baja and San Diego areas, the sample sizes were inconsistently smaller in the other communities like Calexico, limiting comparisons. Future studies would greatly benefit from more consistent and large sample comparisons. Future studies could also include more targeted surveys that compare pairs of border cities (including interviews and focus groups). Qualitative methods could also help identify other indicators not already found in the aforementioned list (Table 5) and also dive deeper into the experiences of border community members regarding those indicators. Panel and cross-sectional data might also aid future studies of border cities residents and their community well-being, especially when looking to conduct assessments over time. Again, the BOP was not longitudinal; yet, future studies should aim to be longitudinal, and QoL research funders should aim to support longitudinal border research approaches. Furthermore, future studies could look at the experiences of individuals who have migrated across U.S.-Mexico border cities and the border as well.

Concluding Remarks

The lack of border-rooted bi-national, multi-community, and multi-indicator social indicators studies keeps policy-makers and researchers operating in the dark. While great work has been done on the individual city-level and with pairs of cities across the U.S.-Mexico border, larger and longitudinal studies are needed. These studies are especially important because disparities continue to exist and shift across borders, and these disparities impact individual QoL and community well-being. Since the BOP, large-scale QoL studies concerning U.S.-Mexico border communities have not occurred, but the BOP and this paper provide a social indicators framework that can be leveraged in future research endeavors (small and large). Additionally, these endeavors can better inform future interventions and policies that impact border communities.

Future research, practice, and policy will need to be culturally relevant; however, such culture and comparisons of culture must be investigated as well. Leaders in all three of these domains will need to work collaborative to achieve QoL and social indicator specific goals. The hope is that this manuscript not only offers a call for larger, comprehensive QoL and social indicator research on the U.S.-Mexico border, but also offers a framework for future research, policy, and practice. The time to reboot this line of research is now.

Notes

Acknowledgements

Special thanks to librarian, Emily Hart, for her help in sourcing articles for this study. Also to Professors S. Guhathakurta, D. Pijawka and E. Sadalla, who developed the Border Observatory Project and produced the empirical database from which this analysis was derived.

Funding

The Border Observatory Project was funded by the Southwest Center for Environmental Research and Policy (SCERP), a consortium of five US universities and ten Mexican universities and research centers, which was supported by the US Congress through the US Environmental Protection Agency.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Agyeman, J. (2005). Sustainable communities and the challenge of environmental justice. New York: New York University Press.Google Scholar
  2. Aldous, T. (1992). Urban villages: A concept for creating mixed-use urban developments on a sustainable scale. London: Urban Villages Group.Google Scholar
  3. Anderson, J. B., & Gerber, J. (2008). Fifty years of change on the U.S.-Mexico border: Growth, development, and quality of life. Austin: University of Texas Press.Google Scholar
  4. Barbaro, M. (2019). What a border sheriff thinks about the wall [audio podcast]. Retrieved 11 January 2019 from https://www.nytimes.com/2019/01/11/podcasts/the-daily/mark-napier-sheriff-border-wall.html. Accessed 16 June 2019.
  5. Barquera, S., Schillinger, D., Aguilar-Salinas, C. A., Schenker, M., Rodríguez, L. A., Hernandez-Alcaraz, C., & Sepulveda-Amor, J. (2018). Collaborative research and actions on both sides of the US-Mexico border to counteract type 2 diabetes in people of Mexican origin. Globalization and Health, 14(1), 84. Retrieved 12 January 2019 from https://globalizationandhealth.biomedcentral.com/articles/10.1186/s12992-018-0390-5. Accessed 16 June 2019.
  6. Barton, H. (2000a). Conflicting perceptions of neighbourhood). In H. Barton (Ed.), Sustainable communities: The potential for eco–neighbourhoods (pp. 3–18). London: Earthscan.Google Scholar
  7. Barton, H. (2000b). The neighbourhood as ecosystem. In H. Barton (Ed.), Sustainable communities: The potential for eco–neighbourhoods (pp. 86–104). London: Earthscan.Google Scholar
  8. Bejarano, C. L., & Shepherd, J. P. (2018). Reflections from the US–Mexico borderlands on a “border-rooted” paradigm in higher education. Ethnicities, 18(2), 277–294. Retrieved 12 January 2019 from http://journals.sagepub.com/doi/pdf/10.1177/1468796817752559?casa_token=Gq4_Sosr6tIAAAAA:HrYBxH2J5OwkHRWGADRAvmjFmBa81JHZxoEizljQ5LHePe5n3nEb1ARXocwQyYKLUy4zMwS-IqzeRQ. Accessed 16 June 2019.
  9. Bolstad, E. (2017). Trump's wall could cause serious environmental damage. Scientific American. Retrieved 11 January 2019 from https://www.scientificamerican.com/article/trumps-wall-could-cause-serious-environmental-damage/. Accessed 16 June 2019.
  10. Borges, G., Cherpitel, C. J., Orozco, R., Zemore, S. E., Wallisch, L., Medina-Mora, M. E., & Breslau, J. (2016). Substance use and cumulative exposure to American society: Findings from both sides of the US–Mexico border region. American Journal of Public Health, 106(1), 119–127.Google Scholar
  11. Burton, E. (2000). The compact city: just or just compact? A preliminary analysis. Urban Studies, 37(11), 1969–2006.  https://doi.org/10.1080/00420980050162184.Google Scholar
  12. Carrillo, G., Patron, M. J. P., Johnson, N., Zhong, Y., Lucio, R., & Xu, X. (2018). Asthma prevalence and school-related hazardous air pollutants in the US-Mexico border area. Environmental Research, 162, 41–48.Google Scholar
  13. Carter, D. E., Peña, C., Varady, R., & Suk, W. A. (1996). Environmental health and hazardous waste issues related to the U.S.-Mexico border. Environmental Health Perspectives, 104(6), 590–594. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1469378/. Accessed 16 June 2019.
  14. Chan, L. Y., Lau, W. L., Lee, S. C., & Chan, C. Y. (2002). Commuter exposure to particulate matter in public transportation modes in Hong Kong. Atmospheric Environment, 36(21), 3363–3373.  https://doi.org/10.1016/S1352-2310(02)00318-7.Google Scholar
  15. Chávez, S. (2011). Navigating the U.S.-Mexico border: the crossing strategies of undocumented workers in Tijuana, Mexico. Ethnic and Racial Studies, 34(8), 1320–1337.  https://doi.org/10.1080/01419870.2010.547586.Google Scholar
  16. Cherpitel, C. J., Ye, Y., Zemore, S. E., Bond, J., & Borges, G. (2015). The effect of cross-border mobility on alcohol and drug use among Mexican-American residents living at the US–Mexico border. Addictive Behaviors, 50, 28–33.Google Scholar
  17. Collins, K. (2013). Insights provided by U.S.-Mexican border quality of life indicators. Eurasia Border Review, 4(1), 43–61. https://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/53302/1/EBR4-1_003.pdf. Accessed 16 June 2019.
  18. Collins, K., & Ley García, J. (2012). Social indicators and measuring sustainability. In Lee, E., & Ganster, P., The U.S.-Mexican border environment: progress and challenges for sustainability (pp. 55–74). SCERP Monograph Series, 16. San Diego State University Press: San Diego.Google Scholar
  19. Collins, K., & Ley García, J. (2014). Happiness and marginalization rates for internal Mexican migrants and the native-born population in Baja California, Mexico. The Social Science Journal, 51(4), 598–606.  https://doi.org/10.1016/j.soscij.2014.07.004.Google Scholar
  20. Coronado, R., & Orrenius, P. M. (2007). Crime on the U.S.-Mexico border: the effect of undocumented immigration and border enforcement. Migraciones Internacionales, 4(1), 39–64. http://www.scielo.org.mx/pdf/migra/v4n1/v4n1a2.pdf. Accessed 16 June 2019.
  21. Dempsey, N., Brown, C., Power, S., & Brown, C. (2011). The social dimension of sustainable development: Defining urban social sustainability. Sustainable Development, 19(5), 389–300.  https://doi.org/10.1002/sd.417.Google Scholar
  22. Dempsey, N., Brown, C., & Bramley, G. (2012). The key to sustainable urban development in UK cities? The influence of density on social sustainability. Progress in Planning, 77(3), 89–141.  https://doi.org/10.1016/j.progress.2012.01.001.Google Scholar
  23. Duran-Encalada, J. A., Paucar-Caceres, A., Bandala, E. R., & Wright, G. H. (2017). The impact of global climate change on water quantity and quality: a system dynamics approach to the US–Mexican transborder region. European Journal of Operational Research, 256(2), 567–581.Google Scholar
  24. Fainstein, S. (2010). The Just City. Ithaca: Cornell University Press.Google Scholar
  25. Feng, S., Krueger, A. B., & Oppenheimer, M. (2010). Linkages among climate change, crop yields and Mexico–U.S. cross-border migration. Proceedings of the National Academy of Sciences, 107(32), 14257–14262.  https://doi.org/10.1073/pnas.1002632107.Google Scholar
  26. Garcini, L. M., Renzaho, A. M., Molina, M., & Ayala, G. X. (2018). Health-related quality of life among Mexican-origin Latinos: the role of immigration legal status. Ethnicity & Health, 23(5), 566–581.Google Scholar
  27. Gomez, A., Gillum, J., & Johnson, K. (2011). U.S. border cities prove havens from Mexico's drug violence. USA Today (18 July 2011). Retrieved from https://usatoday30.usatoday.com/news/washington/2011-07-15-border-violence-main_n.htm. Accessed 16 June 2019.
  28. González, D. (2017). 4 reasons Mexico hates Trump’s border wall. USA Today. Retrieved 11 January 2019 from: https://www.usatoday.com/story/news/nation-now/2017/01/27/reasons-mexico-hates-border-wall/97128754/. Accessed 16 June 2019.
  29. Guhathakurta, S., Pijawka, D., & Sadalla, E. (2010). The Border Observatory Project: The State of the U.S.–Mexico Border Cities. Scottsdale: Arizona State University.Google Scholar
  30. Gutiérrez-Vega, M., Esparza-Del Villar, O. A., Carrillo-Saucedo, I. C., & Montañez-Alvarado, P. (2018). The possible protective effect of marital status in quality of life among elders in a US-Mexico border city. Community Mental Health Journal, 54(4), 480–484.Google Scholar
  31. Hagen, B., Nassar, C., & Pijawka, D. (2017). The social dimension of sustainable neighborhood design: comparing two neighborhoods in Freiburg, Germany. Urban Planning, 2(4), 64–80.  https://doi.org/10.17645/up.v2i4.1035.Google Scholar
  32. Hamiduddin, I. (2015). Social sustainability, residential design and demographic balance: Neighbourhood planning strategies in Freiburg, Germany. Town Planning Review, 86(1), 29–52.  https://doi.org/10.3828/tpr.2015.3.Google Scholar
  33. Handley, M. A., & Sudhinaraset, M. (2017). The important role of binational studies for migration and Health Research: a review of US-Mexico binational studies and design considerations for addressing critical issues in migrant health. International Migration, 55(5), 75–121.Google Scholar
  34. Hargrove, W. L., Del Rio, M., & Korc, M. (2018). Water matters: water insecurity and inadequate sanitation in the US/Mexico border region. Environmental Justice, 11(6), 222–227.Google Scholar
  35. Harvey, D. (2010). Social justice and the City. Athens: The University of Georgia Press.Google Scholar
  36. Henderson, D. E., Milford, J. B., & Miller, S. L. (2005). Prescribed burns and wildfires in Colorado: Impacts of mitigation measures on indoor air particulate matter. Journal of the Air & Waste Management Association, 55(10), 1516–1526.  https://doi.org/10.1080/10473289.2005.10464746.Google Scholar
  37. Herzog, L. A., & Sohn, C. (2017). The co-mingling of bordering dynamics in the San Diego–Tijuana cross-border metropolis. Territory, Politics, Governance, Online First. Retrieved 12 January 9 from  https://doi.org/10.1080/21622671.2017.1323003.
  38. Hilfinger Messias, D. K., Sharpe, P. A., del Castillo-González, L., Treviño, L., & Parra-Medina, D. (2017). Living in limbo: Latinas' assessment of lower Rio Grande Valley Colonias communities. Public Health Nursing, 34(3), 267–275.Google Scholar
  39. Jones, R. (2015). Migration pessimism and the subjective well-being of migrant households in Mexico. Bulletin of Latin American Research, 34(3), 305–323.  https://doi.org/10.1111/blar.12265.Google Scholar
  40. Kapucu, N. (2011). Social capital and civic engagement. International Journal of Social Inquiry, 4(1), 23–43. http://illinois-online.org/krassa/ps410/Readings/Kapucu, Social Capital and Civic Engagement.pdf. Accessed 16 June 2019.
  41. Kutner, B. A., Nelson, K. M., Simoni, J. M., Sauceda, J. A., & Wiebe, J. S. (2017). Factors associated with sexual risk of HIV transmission among HIV-positive Latino men who have sex with men on the US-Mexico border. AIDS and Behavior, 21(3), 923–934.Google Scholar
  42. Lasky, J. R., Jetz, W., & Keitt, T. H. (2011). Conservation biogeography of the US–Mexico border: a transcontinental risk assessment of barriers to animal dispersal. Diversity and Distributions, 17(4), 673–687.  https://doi.org/10.1111/j.1472-4642.2011.00765.x.Google Scholar
  43. Lee, S. J., & Kim, Y. (2018). Economy doesn’t buy community wellbeing: a study of factors shaping community wellbeing in South Korea. International Journal of Community Well-Being, 1(1), 33–44.Google Scholar
  44. Liverman, D. M., Varady, R. G., Chavez, O., & Sanchez, R. (1999). Environmental issues along the United States-Mexico border: Drivers of change and responses of citizens and institutions. Annual Review of Energy and the Environment, 24(1), 607–643.Google Scholar
  45. Long, H. (2018). U.S., Canada and Mexico just reached a sweeping new NAFTA deal. Here’s what’s in it. The Washington Post. Retrieved 11 January 2019 from https://www.washingtonpost.com/business/2018/10/01/us-canada-mexico-just-reached-sweeping-new-nafta-deal-heres-whats-it/?utm_term=.ca2ce6004d4f. Accessed 16 June 2019.
  46. Marquez-Velarde, G., Grineski, S., & Staudt, K. (2015). Mental health disparities among low-income US Hispanic residents of a US-Mexico border Colonia. Journal of Racial and Ethnic Health Disparities, 2(4), 445–456.Google Scholar
  47. McAslan, D., Prakash, M., Pijawka, D., Guhathakurta, S., & Sadalla, E. (2013). Measuring quality of life in border cities: The border observatory project in the US-Mexico border region. In Sirgy, M. J., Phillips, R., & Rahtz, D (eds.), Community quality-of-life indicators: Best cases VI (pp. 143–169). Springer, Dordrecht.Google Scholar
  48. Mier, N., Ory, M. G., Zhan, D., Conkling, M., Sharkey, J. R., & Burdine, J. N. (2008). Health-related quality of life among Mexican Americans living in colonias at the Texas–Mexico border. Social Science & Medicine, 66(8), 1760–1771. https://www.ncbi.nlm.nih.gov/pubmed/18261832. Accessed 16 June 2019.
  49. Milbrath, L. W. (1982). A conceptualization and research strategy for the study of ecological aspects of the quality of life. Social Indicators Research, 10(2), 133–157.  https://doi.org/10.1007/BF00300833.Google Scholar
  50. Molokwu, J. C., Penaranda, E., & Shokar, N. (2017). Decision-making preferences among older Hispanics participating in a colorectal cancer (CRC) screening program. Journal of Community Health, 42(5), 1027–1034.Google Scholar
  51. Montoya-Galvez, C. (2018). Migrant child dies in border patrol custody; second in a month. CBS News. Retrieved 11 January 2019 from: https://www.cbsnews.com/news/migrant-child-dies-in-border-patrol-custody-today-2018-12-25/. Accessed 16 June 2019.
  52. Moya, E.M., Chavez-Baray, S.M., Loweree, J., Mattera, B., & Martinez, N., (2017). Adults experiencing homelessness in the us–Mexico border region: a Photovoice project. Frontiers in Public Health, 5(113), Retrieved 12 January 2019 from https://www.frontiersin.org/articles/10.3389/fpubh.2017.00113/full. Accessed 16 June 2019.
  53. Norman, L. M., Villarreal, M. L., Lara-Valencia, F., Yuan, Y., Nie, W., Wilson, S., Amaya, G., & Sleeter, R. (2012). Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.–Mexico borderlands. Applied Geography, 34, 413–424.  https://doi.org/10.1016/j.apgeog.2012.01.006.Google Scholar
  54. Nowotny, K. M., Cepeda, A., Perdue, T., Negi, N., & Valdez, A. (2017). Risk environments and substance use among Mexican female sex work on the US–Mexico border. Journal of Drug Issues, 47(4), 528–542.Google Scholar
  55. O'Connor, K., Anders, R. L., Balcazar, H., Ibarra, J., Perez, E., Flores, L., Ortiz M. & Bean, N. H. (2008). Prevalence of mental health issues in the borderlands: a comparative perspective. Hispanic Health Care International, 6(3), 140–149. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4218741/. Accessed 16 June 2019.
  56. Peña, D. G. (1997). The terror of the machine: technology, work, gender, and ecology on the U.S.-Mexico border. Austin: University of Texas Press.Google Scholar
  57. Peña, J. M., Garcini, L. M., Gutierrez, A. P., Ulibarri, M. D., & Klonoff, E. A. (2017). Traumatic events and symptoms among Mexican deportees in a border community. Journal of Immigrant & Refugee Studies, 15(1), 36–52.Google Scholar
  58. Perkins, D. D., Hughey, J., & Speer, P. W. (2002). Community psychology perspectives on social capital theory and community development practice. Community Development, 33(1), 33–52.Google Scholar
  59. Pijawka, D., Guhathakurta, S., Sadalla, E., Collins, K., Prakash, M., & McAslan, D. (2012). Urban indicators for border areas. In E. A. Cook & J. J. Lara (Eds.), Remaking Metropolis: Global challenges of the urban landscape (pp. 103–121). New York: Routledge.Google Scholar
  60. Pstross, M., Talmage, C. A., & Knopf, R. C. (2014). A story about storytelling: enhancement of community participation through catalytic storytelling. Community Development, 45(5), 525–538.  https://doi.org/10.1080/15575330.2014.955514.Google Scholar
  61. Rosales, C. B., de Zapien, J. E. G., Chang, J., Ingram, M., Fernandez, M. L., Carvajal, S. C., & Staten, L. K. (2017). Perspectives on a US-Mexico border Community's diabetes and" health-care" access mobilization efforts and comparative analysis of community health needs over 12 years. Frontiers in Public Health, 5, 152–152.Google Scholar
  62. Ruiz-Beltran, M., & Kamau, J. K. (2001). The socio-economic and cultural impediments to well-being along the U.S.-Mexico border. Journal of Community Health, 26(2), 123–132.  https://doi.org/10.1023/A:1005229330204.Google Scholar
  63. Sanchez, G. (2018). ‘Circuit children’: The experiences and perspectives of children engaged in migrant smuggling facilitation on the US-Mexico border. Anti-Trafficking Review, (11). Retrieved 12 January 2019 from https://www.antitraffickingreview.org/index.php/atrjournal/article/download/353/294. Accessed 16 June 2019.
  64. Semple, S. J., Stockman, J. K., Goodman-Meza, D., Pitpitan, E. V., Strathdee, S. A., Chavarin, C. V., et al. (2017). Correlates of sexual violence among men who have sex with men in Tijuana, Mexico. Archives of Sexual Behavior, 46(4), 1011–1023.Google Scholar
  65. Shepard, S. (2019). Poll: Voters blame Trump, GOP for shutdown. Politico. Retrieved 11 January 2019 from: https://www.politico.com/story/2019/01/08/poll-voters-blame-trump-gop-for-shutdown-1088207. Accessed 16 June 2019.
  66. Sirgy, J. M. (2018). What types of indicators should be used to capture community well-being comprehensively? International Journal of Community Well-Being, 1(1), 3–9.Google Scholar
  67. Slack, J., Martínez, D. E., Lee, A. E., & Whiteford, S. (2016). The geography of border militarization: violence, death and health in Mexico and the United States. Journal of Latin American Geography, 15(1), 7–32.  https://doi.org/10.1353/lag.2016.0009.Google Scholar
  68. Sohn, C. (2014). Modelling cross-border integration: the role of Borders as a resource. Geopolitics., 19, 587–608.  https://doi.org/10.1080/14650045.2014.913029.Google Scholar
  69. Soler, A., & Beatrice, J. S. (2018). Expanding the role of forensic anthropology in a humanitarian crisis: an example from the USA-Mexico border. In Sociopolitics of migrant death and repatriation (pp. 115–128). Cham: Springer.Google Scholar
  70. Sonmez, F., & Wagner, J. (2019). Shutdown showdown: Democrats press to reopen government as Trump heads to border. The Washington Post. Retrieved 11 January 2019 from https://www.washingtonpost.com/politics/shutdown-showdown-trump-heads-to-the-border-as-impasse-over-wall-drags-on/2019/01/10/bb325c92-14c9-11e9-90a8-136fa44b80ba_story.html?utm_term=.9d94d79109d4. Accessed 16 June 2019.
  71. Sosa, O. (2008). Border planning in the San Diego-Tijuana region: local planning and national policy. Berkeley Planning Journal, 21(1), 169–185. https://cloudfront.escholarship.org/dist/prd/content/qt5th0w62n/qt5th0w62n.pdf?t=m4yjjk. Accessed 16 June 2019.
  72. Statista.com (2014). Percentage of households owning a car in selected countries in 2014, by country. Retrieved 12 March 2017 from: https://www.statista.com/statistics/516280/share-of-households-that-own-a-passenger-vehicle-by-country/. Accessed 16 June 2019.
  73. Sullivan, E., & Olmedo, C. (2015). Informality on the urban periphery: housing conditions and self-help strategies in Texas informal subdivisions. Urban Studies, 52(6), 1037–1053.Google Scholar
  74. Sung, H., & Phillips, R. G. (2018). Indicators and community well-being: exploring a relational framework. International Journal of Community Well-Being, 1(1), 63–79.Google Scholar
  75. Svendsen, E. R., Gonzales, M., & Commodore, A. (2018). The role of the indoor environment: residential determinants of allergy, asthma and pulmonary function in children from a US-Mexico border community. Science of the Total Environment, 616, 1513–1523.Google Scholar
  76. Talmage, C. A. (2012). Tourism resources and opportunities: Assessment for Nogales, Arizona. ASU Center for sustainable tourism, College of Public Programs, Arizona State University. Technical Report. Retrieved from https://tinyurl.com/y957xkpv. Accessed 16 June 2019.
  77. Talmage, C. A., & Frederick, C. (2019). Quality of life, multimodality, and the demise of the autocentric metropolis: A multivariate analysis of 148 mid-size US cities. Social Indicators Research, 141(1), 365–390.Google Scholar
  78. Talmage, C. A., Peterson, C. B., & Knopf, R. C. (2017). Punk rock wisdom: an emancipative psychological social capital approach to community well-being. In Handbook of community well-being research (pp. 11–38). Dordrecht: Springer.Google Scholar
  79. Talmage, C. A., Figueroa, H. L., & Wolfersteig, W. L. (2018a). Perceptions of expanded shared use: a mixed method examination of pathways and barriers to community empowerment, health and well-being. School Community Journal, 28(2), 297–320. Retrieved 12 January 2019 from http://www.schoolcommunitynetwork.org/SCJ.aspx. Accessed 16 June 2019.
  80. Talmage, C., Hagen, B., Pijawka, D., & Nassar, C. (2018b). Measuring neighborhood quality of life: placed-based Sustainability indicators in Freiburg, Germany. Urban Science, 2(4), 106. Retrieved 12 January 2019 from https://www.mdpi.com/2413-8851/2/4/106/pdf. Accessed 16 June 2019.
  81. Texas Secretary of State. (2017). What is a Colonia? Retrieved August 26, 2017 from https://www.sos.state.tx.U.S./border/colonias/what_colonia.shtml. Accessed 16 June 2019.
  82. Tzeng, G. H., Lin, C. W., & Opricovic, S. (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy, 33(11), 1373–1383.  https://doi.org/10.1016/j.enpol.2003.12.014.Google Scholar
  83. Varady, R. G., Scott, C. A., Wilder, M., Morehouse, B., Pablos, N. P., & Garfin, G. M. (2013). Transboundary adaptive management to reduce climate-change vulnerability in the western U.S.–Mexico border region. Environmental Science & Policy, 26, 102–112.  https://doi.org/10.1016/j.envsci.2012.07.006.Google Scholar
  84. Vasquez, G., Salinas, J., Molokwu, J., Shokar, G., Flores-Luevano, S., Alomari, A., & Shokar, N. (2018). Physical activity in older Mexican Americans living in two cities on the US-Mexico border. International Journal of Environmental Research and Public Health, 15(9), 1820. Retrieved 12 January 2019 from https://www.mdpi.com/1660-4601/15/9/1820/pdf. Accessed 16 June 2019.
  85. Vela, M. R., Lind, S. E., & Gutierrez, P. H. (2018). Determining pathways and connections between access to water and high school noncompletion rates for communities along the US–Mexico border. Journal of Social Change, 10(1), 105–117.Google Scholar
  86. Warren, R., & Kerwin, D. (2017). The 2,000 Mile Wall in search of a purpose: since 2007 visa overstays have outnumbered undocumented border crossers by a half million. Journal on Migration and Human Security, 5(1), 124–178. http://jmhs.cmsny.org/index.php/jmhs/article/view/77. Accessed 16 June 2019.
  87. Weigel, M. M., & Armijos, R. X. (2018). Food insecurity, Cardiometabolic health, and health care in US-Mexico border immigrant adults: An exploratory study. Journal of Immigrant and Minority Health.  https://doi.org/10.1007/s10903-018-0817-3.
  88. Welzel, C., Inglehart, R., & Deutsch, F. (2005). Social capital, voluntary associations and collective action: which aspects of social capital have the greatest ‘civic’ payoff? Journal of Civil Society, 1(2), 121–146.Google Scholar
  89. Western Sustainability and Pollution Prevention Network (WSPPN) (2017). U.S.-Mexico Border. Retrieved August 26, 2017 from http://wsppn.org/resources/u-s-mexico-border/. Accessed 16 June 2019.
  90. Wilder, M., Scott, C. A., Pablos, N. P., Varady, R. G., Garfin, G. M., & McEvoy, J. (2010). Adapting across boundaries: climate change, social learning, and resilience in the U.S.–Mexico border region. Annals of the Association of American Geographers, 100(4), 917–928.  https://doi.org/10.1080/00045608.2010.500235.Google Scholar
  91. Wilder M., Garfin, G., Ganster, P., Eakin, H., Romero-Lankao, P., Lara-Valencia, F., Cortez-Lara, A.A., Mumme, S., Neri, C., Muñoz-Arriola, F., &Varady, R.G. (2013) Climate change and U.S.-Mexico border communities. In: Garfin G., Jardine A., Merideth R., Black M., LeRoy S. (eds) Assessment of climate change in the Southwest United States. NCA Regional Input Reports. Island Press, Washington, DC.  https://doi.org/10.5822/978-1-61091-484-0_16.
  92. Winter, J., & Farthing, S. (1997). Coordinating facility provision and new housing development: Impacts on car and local facility use. In S. M. Farthing (Ed.), Evaluating local environmental policy (pp. 159–179). Aldershot: Avebury.Google Scholar
  93. Zuckerman, M. J., Schmulson, M. J., Bashashati, M., Jia, Y., Dwivedi, A., Ortiz, M., et al. (2018). Irritable bowel syndrome on the US Mexico border. Journal of Clinical Gastroenterology, 52(7), 622–627.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Hobart and William Smith CollegesGenevaUSA
  2. 2.School of Geographical Sciences and Urban PlanningArizona State UniversityTempeUSA

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