Neoliberal Housing and the Health-Poverty Nexus: Mapping of Evidence using a Systematic Framework Synthesis from Argentina and Chile

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While existing reviews often link housing conditions to health outcomes, few consider the structural effects of neoliberal reforms that reframe housing as a commodity rather than a fundamental human need and a critical factor in health. Drawing on a framework synthesis of twenty-two studies from Argentina and Chile, we identify the institutional, spatial, and social mechanisms through which housing systems affect resident well-being. Using a structured matrix built on the PISO framework and informed by PRISMA guidelines, we analyse evidence across four interlinked domains: health, economic resilience, social cohesion, and urban spatial integration. Our findings reveal that neoliberal housing programs frequently externalise structural risks to residents, exacerbating vulnerability despite formal homeownership. The paper also introduces a bespoke risk of bias tool adapted for mixed-methods research, revealing pervasive gaps in methodological transparency of articles reviewed here. By integrating health into a broader structural critique, this review contributes to both the social housing and public health literature, demonstrating how market-led policies may entrench poverty rather than disrupt it. PROSPERO ID CRD42024602433. Housing and health Latin America framework synthesis social determinants of health neoliberal housing policies Argentina Chile Figures Figure 1 Introduction Systematic reviews from high-income countries consistently demonstrate that stable, affordable, and quality housing is associated with improved mental and physical health outcomes for low-income populations. For example, Braveman et al. ( 2011 ) found that affordable housing reduces psychological stress and supports better overall health, particularly among families at risk of homelessness. Similarly, housing interventions such as homeless shelters have been shown to significantly reduce anxiety, depression, and substance abuse disorders in homeless individuals (Rog et al., 2014 ). Improvements in housing conditions, such as better ventilation, lead removal, and insulation, are also associated with reductions in respiratory diseases like asthma (Krieger & Higgins, 2002 ; Thomson et al., 2009 ). Systematic reviews that include studies from Low and Middle Income Countries (LMIC) reveal that poor housing conditions pose severe health risks, particularly in the form of infectious diseases such as tuberculosis, cholera, and malaria (Vlahov et al., 2007 ). For instance, a review by Lilford et al. ( 2017 ) highlights that housing interventions in slum areas, such as upgrading sanitation infrastructure and improving access to clean water, can reduce the prevalence of diarrheal diseases and other waterborne illnesses, which are a leading cause of mortality in these regions. Moreover, systematic reviews emphasise that interventions focusing on housing affordability and security are crucial for improving mental health in LMICs. Indeed, a study by Weimann and Oni ( 2019 ) found that lack of secure tenure in informal settlements is linked to increased levels of stress and anxiety, as residents live under constant threat of eviction. In such contexts, housing security policies, including land tenure reforms and slum upgrading projects, have been shown to alleviate some of the psychological burdens associated with housing instability (Baker et al., 2017 ). Despite the growing recognition of the links between housing and health and the perpetuation of the poverty cycle, the above research lacks understanding of the structural implications of neoliberal housing policies. Most studies fail to critically engage with the broader economic and political frameworks brought by neoliberalism in housing such as the retreat of the state from housing provision that has deepened the structural inequities that affect health outcomes (Satterthwaite et al., 2020 ). For instance, and as shown this far, while there is substantial evidence linking poor housing conditions with adverse health outcomes in LMIC, there is limited research on how neoliberal housing policies, such as the reliance on private-sector for housing solutions, might affect housing instability and health inequities. Furthermore, the market-oriented approach of neoliberal policies tends to overlook the broader social and health needs of low-income populations, focusing instead on housing as an economic commodity rather than as a human right or a public health imperative. In countries like Chile, this shift has left many low-income families with a new problem of families owning a house but still in poverty (Rodriguez and Sugranyes, 2004 ). Notwithstanding, there are contextual factors that might mitigate the impact of neoliberal policies. For example community cohesion and social ties can help low-income families navigate housing insecurity, access informal economies, and pool resources to maintain housing stability. Research has shown that in tightly knit communities, residents are more likely to engage in collective action to prevent evictions, advocate for housing rights, or secure basic services such as water and sanitation (Mitlin, 2015 ). Such initiatives help to soften the negative impacts of neoliberal policies, reducing housing insecurity and improving health outcomes by providing more stable living conditions and a sense of security. Likewise, the degree of urban connectivity and access to job opportunities is another critical factor. Neoliberal housing policies in LMICs mostly support home ownership via the provision of subsidies, benefits that can only be accessed via a demonstrable and steady income (Murray and Clapham, 2015). Access to employment is therefore crucial for maintaining housing stability. Research in Latin American cities like São Paulo and Mexico City shows that low-income families in better-connected neighbourhoods are more likely to experience upward mobility and improved living conditions despite facing high housing costs (Caldeira, 2017 ; Schteingart & Salazar, 2018 ). These contextual factors, community cohesion and urban connectivity, highlight the importance of considering local social dynamics and infrastructure in the systematic review approaches. As Baker and Mason ( 2012 ) argue, without an understanding of these broader policy dynamics, efforts to improve health outcomes through housing interventions may be piecemeal and unsustainable. Review Objective : Filling this research gap requires moving beyond a narrow focus on individual housing interventions to examine the broader structural impacts of neoliberal housing reforms on household health and poverty. In this review, the nexus centres around the cycle of poverty that affordable housing policies aim to solve: People who live in poverty often struggle to afford safe and suitable housing. They may live in overcrowded, unsafe, or unsanitary conditions, which can lead to a variety of health problems. In addition, inadequate housing can make it more difficult for people to find and maintain employment, which can perpetuate the cycle of poverty (several authors describe the housing-health and poverty nexus, for developed economies see Kemp, 2017 and Dewilde, 2021 . For LMIC see Davis, 2007 and Zadeh et al, 2021 ). This calls for a more holistic methodological approach that centring on the intersection of housing and health in the cycle of poverty, looks at the contextual factors that might mitigate the impact of neoliberal housing policies, such as connectivity to jobs and community cohesion. Acknowledging this research gap, this systemic review therefore asks: What factors explain increasing/decreasing benefits of neoliberal housing policies amongst low income families in Argentina and Chile? Methodology Framework synthesis is a method used in systematic reviews to integrate existing qualitative research by mapping data onto an a priori framework, often based on theories or concepts from previous research (Brunton et al, 2020 ). As the authors explain, the approach involves first identifying key categories in the framework which provides a ‘scaffold’ against which the data is organised. Then coding and categorising data from included studies to fit these categories. For the purpose of our study, the team developed an a priori thematic framework, informed by both theoretical constructs (e.g., health-poverty nexus, urban inequality) and preliminary scoping of the literature. In alignment with the PRISMA 2020 guidelines for systematic reviews and the PRISMA Extension for Scoping Reviews (PRISMA-ScR), the adopted method preserves the core principles of systematic synthesis, transparency, replicability, and methodological rigour, while allowing for conceptual flexibility appropriate to complex, interdisciplinary evidence bases. The framework functioned as a coding scaffold, enabling structured comparison across diverse study types and thematic domains (health, economy, cohesion, and urban space), consistent with guidance for qualitative and mixed-methods integration in systematic reviews (Harden & Thomas, 2005 ; Thomas & Harden, 2008 ). Table 1 Thematic framework Themes Factors Equality Inequality Economic Health Cohesion/sociability Isolation Community Integration Sprawl/gentrification Urban Space Domain being studied: (identifying key concepts) The primary focus of this paper is to thematically and systematically evaluate the factors identified by the literature that explain increasing/decreasing benefits of neoliberal housing policies amongst low income families in Argentina and Chile since the start of their respective neoliberal housing regimes. There are several frameworks to identify key concepts with the most popular one being the Population, Intervention, Comparison, Outcome (PICO) framework used in health studies. In order to cover for the geographical component of our review, we have adapted the framework to Population, Intervention, Setting and Outcomes (PISO). Table 2 below presents the framework adopted for this review. Table 2 Framework for key concept identification POPULATION Low income families in Argentina and Chile INTERVENTION Neoliberalism SETTING Social housing schemes in cities (defined as urban agglomerations of more than 250,000 inhabitants) OUTCOME Economic/health equality; community cohesion and urban integration Search terms and strategy : The search terms were compiled by two methods: generating terms based on meaning (using synonyms or closely related concepts) and by grammar (plurals), by style (acronyms, abbreviations, professional jargon). The team also gathered terms from publications retrieved during the testing of the methodology, collecting key words assigned to articles. The team also added controlled vocabulary adapted from each database that was mined. Additional file 1 compiles all search terms used by the team. The team mined the following repositories: Scopus, WebofScience and PubMed in English and Spanish. Dates were limited to the time when neoliberal housing regimes were implemented in both countries (1990) to publications available until December 2023. For a more comprehensive search the team used a text word search (title, abstract and any other part of the text). Additional file 2 shows the search strategies implemented in all repositories. Types of studies included : The review includes descriptive impact studies examining factors explaining increasing/decreasing benefits of neoliberal housing policies using quantitative, qualitative or mixed-methods. Thus reflecting the multi-dimensional nature of housing policy impacts. Data extraction and data synthesis strategy : The team used the EPPI reviewer software to facilitate article screening, appraisal and data extraction, using EPPI’s collaborative cloud platform. After importing the searches, duplicates were automatically removed (i.e. same publication found in different databases) with a manual check by the entire team to minimise software/human error. Articles were then distributed to all four team members, to be screened by title and abstract using the pre-established protocol. Each article was screened by at least two team members, if there were disagreements, a third team member reviewed the data and agreed on its inclusion/exclusion. The full text of selected articles was then read to determine inclusion in the final thematic synthesis. The team held an online workshop to collectively agree on final decision of all excluded articles. At this point, the team collected data for the PRSIMA report, ensuring that exclusions were justified and all articles accounted for. Graphic 1: PRISMA Report A data extraction spreadsheet was used at this stage covering citation details, population, geographical coverage, study purpose and aims, research methods used including data collection and analytical approach, detail of themes, outcomes and relevant quotations findings (if any) in relation to the outcomes, conclusions and limitations. The textual analysis of final selection of papers followed line by line coding (Harden and Thomas, 2005 ) for their categorisation in the pre-established thematic framework (Table 1 ). The content of these themes was then synthesised trying to keep as close as possible to the original text used by the authors and considering the emerging factors reported by the authors that explain increasing/decreasing benefits of neoliberal housing policies. Risk of bias : The critical appraisal checklist is a widely used method by researchers conducting systematic reviews (Tod et al 2021 ). This includes tools such as the Critical Appraisal Skills Programme (CASP), the Consolidated Criteria for Reporting Qualitative Research (COREQ) tool, and the Standards for Reporting Qualitative Research (SRQR) tool. Given the inclusion of quantitative, qualitative, and mixed-methods studies, we developed a bespoke risk of bias tool adapted from existing validated frameworks. Each domain in our tool was justified based on relevance to the methodological diversity of the included studies and tailored to assess key quality criteria, such as study design appropriateness, data collection rigour, sample transparency, and reporting of confounding variables. To ensure internal consistency and usability, the tool was piloted on a subset of five diverse studies representing different methodological types (qualitative, quantitative, mixed). Based on this pilot, minor refinements were made to scoring instructions and domain definitions. This piloting process functioned as a form of face and content validation, appropriate for context-specific appraisal tools in reviews of complex social interventions (Harden & Thomas, 2005 ; Tod et al., 2021 ). While the tool is not externally validated, its transparent development process and clear scoring logic ensured consistent application across all included studies, supported by reviewer consensus procedures. Additional file 3 lists all variables and their justification for inclusion as well as the resulting risk of bias assessment template used by the team. During implementation, each article was assessed by two team members, awarding a score of 1 for each appropriately addressed variable and 0 when not. A subsequent online workshop was held to agree on final scores and determine the weighting for each risk of bias criterion. Given the diversity of study types, the weighting for sample size was set at 15%, allowing fair consideration of purely qualitative studies that used small samples but conducted in-depth interviews with a variety of stakeholders (i.e., from government level to homeowners). Study design was weighted at 50%, allowing nuanced consideration of the different study types and research questions presented by all authors. Similarly, data collection was weighted at 30%, while confounding factors had a collective weighting of 5% (i.e., Household Income/Employability, Pre-existing Health Conditions, Educational Level, Urban Infrastructure/Access to Services, High Crime Rates, Housing Market Conditions), each awarded one point when reported and half point if only mentioned but not reported, with the resulting sum weighted by 5%. Results and Discussion Mapping the Scope and Biases of the Existing Literature The analysis of the twenty-two studies included in this systematic review reveals important insights into both the scope and limitations of existing research in Argentina and Chile. By mapping the key characteristics of these studies, such as geographic distribution, settlement demographics, and methodological choices, this section highlights and discusses both the areas of scholarly concentration and notable gaps in the literature. Of the entire dataset, nineteen settlements (86% of total) are located in Chile, and three settlements (14%) are in Argentina (See Table 3 below). A significant geographical imbalance is immediately apparent with the vast majority of studies concentrated Chile and in the Santiago Metropolitan Region. This alone accounts for 60% of the Chilean cases, while the rest are dispersed across Valparaíso, Concepción, and Tarapacá. In contrast, the only three cases in Argentina are all in different locations, spanning Buenos Aires, La Pampa, and Santa Fe. This skewed distribution suggests a strong academic emphasis on the Chilean experience with neoliberal housing policies, potentially driven by the country's pioneering role in adopting neoliberal reforms in Latin America in the late 1980’s (Murray and Clapham, 2015). However, it also underscores a substantial research gap in the Argentine context, limiting the ability to conduct broader comparative analyses across diverse national frameworks and limiting generalisability. In terms of settlement scale, the majority of studies (59%) examine communities with over 500 residents, while 34% focus on smaller housing schemes ranging between 101 and 500 residents. Only two papers focus at the housing scheme level of less than 100 residents (see Scale column in Table 3 ). This differentiation may reflect divergent housing challenges in urban versus peri-urban areas, but it also raises questions about the generalisability of the findings across different spatial and demographic contexts. Table 3 Mapping of dataset results Publication ID Area covered Scale Region Country Baeza et al., (2021) Neighbourhood > 500 Santiago & Valparaiso Chile Burgos (2015) Commune 101–500 Tarapacá Chile Cáceres et al., ( 2001 ) Commune 101–500 Santiago Chile Carrasco ( 2021 ) Housing scheme 500 Santiago Chile Cutts ( 2015 ) City > 500 Santa Fe Argentina Dohnke (2015) City > 500 Santiago Chile Flores-Larsen ( 2021 ) Housing scheme 101–500 La Pampa Argentina Fuentes y Rodriguez (2020) City > 500 Santiago Chile Fuster-Farfán ( 2020 ) Housing scheme > 500 Santiago Chile Gill (2022) Housing scheme > 500 Santiago Chile Inzunza y Cárdenas (2017) Neighbourhood > 500 Maule Chile Lehner ( 2021 ) Housing scheme 101–500 Buenos Aires Argentina Orlando-Romero (2023) Neighbourhood > 500 Valparaíso Chile Ozler ( 2012 ) Neighbourhood 101–500 Santiago Chile Perez (2017) Commune > 500 Santiago Chile Perez ( 2018 ) Housing scheme > 500 Santiago Chile Porras-Salazar (2020) Housing scheme 101–500 Concepcion Chile Rioseco (2008) City 101–500 Santiago Chile Stang et al., ( 2022 ) City > 500 Santiago & Antofagasta Chile Torres et al., ( 2008 ) Commune 101–500 Santiago Chile Vergara (2019) Housing scheme > 500 Santiago Chile Zunino, Hidalgo ( 2009 ) City < 100 Valparaiso Chile Regarding methodology, twelve of the twenty-two analysed articles rely purely on qualitative data with only 4 using quantitative whilst 6 use mixed methods (See Table 4 ). Qualitative depth appears to be pursued primarily through interviews complemented with other forms of data collection including household or neighbourhood surveys using field work observations. From all the studies using interviews, only six of them provide data on both the number of people interviewed and the total population of the study, making it challenging to assess the proportion of the population represented in the sample. Still, all six articles report that more than 75% of the population was interviewed. However, the absence of standardised reporting protocols across studies hinders efforts to assess the validity and representativeness of these research findings. Table 4 Mapping of research methods and risk of bias score Publication ID Method Primary data Secondary data Score Burgos (2015) Qualitative Population surveys Government documents and reports 1.13 Cáceres et al., ( 2001 ) Mixed Population surveys Government documents and reports 0.85 Carrasco ( 2021 ) Mixed Interviews and physical survey Government documents and reports 1.05 Celhay ( 2020 ) Quantitative Interviews and population surveys Government documents and reports 1.18 Cutts ( 2015 ) Qualitative Interviews and physical survey Government documents and reports 0.85 Dohnke (2015) Quantitative n/a Relevant housing market data 0.95 Flores-Larsen ( 2021 ) Quantitative household survey Relevant indexes and benchmarks 1 Fuentes y Rodriguez (2020) Mixed N/a Census (CASEN) 0.98 Fuster-Farfán ( 2020 ) Qualitative Interviews Government documents and reports 0.85 Gill (2022) Mixed Interviews and population survey Government documents and reports 1.05 Inzunza y Cárdenas (2017) Mixed Interviews Spatial data 0.35 Lehner ( 2021 ) Qualitative Interviews Legal docs and construction reports 1.05 Orlando-Romero (2023) Qualitative Interviews and focus groups Government documents and reports 0.9 Ozler ( 2012 ) Qualitative Interviews and physical survey Government documents and reports 0.88 Perez (2017) Qualitative Interviews and physical survey Government documents and reports 0.8 Perez ( 2018 ) Qualitative Interviews and physical survey Spatial data 0.85 Porras-Salazar (2020) Quantitative Population surveys Relevant meteorological data 0.88 Rioseco (2008) Qualitative Population surveys Government documents and reports 0.98 Stang et al., ( 2022 ) Qualitative Interviews Government documents and reports 0.9 Torres et al., ( 2008 ) Qualitative Population surveys Relevant statistics 1.1 Vergara et al ( 2019 ) Qualitative Interviews Government documents and reports 0.88 Zunino, Hidalgo ( 2009 ) Mixed Interviews Census and spatial data 0.98 Altogether, the review reveals a literature that is rich in case studies, particularly in Chilean urban contexts, but constrained by geographic and methodological concentration. The predominance of Santiago-based studies, along with a reliance on select methodological tools and inconsistent reporting, suggests the need for broader, more diversified research efforts. Addressing these gaps could involve targeted studies in underrepresented regions, increased attention to smaller and non-urban settlements, and the adoption of more rigorous standards for data collection and reporting. Such measures are essential for advancing a more comprehensive and comparative understanding of how neoliberal housing policies are reshaping urban and peri-urban life in both countries. Narrative synthesis : Following the thematic framework for this paper (Table 1 ), this section now presents the results of the increasing/decreasing benefits of neoliberal housing policies in Chile and Argentina. All papers included in this section reported on the specific outcomes of a social housing scheme delivered under neoliberal policies, with the reported outcomes divided into: health, economy, social cohesion, and urban space. Health : The results summarised in Table 5 show that one of the most persistent negative outcomes of neoliberal housing policies lies in their detrimental health impacts, which, in turn, deepen poverty cycles. Carrasco and O’Brien ( 2021 ) explore the long-term health impacts of incremental social housing schemes in Quinta Monroy, Iquique , Chile. They found that unregulated housing extensions led to a deterioration in living conditions, including poor ventilation and lighting, overcrowding, and increased safety risks, all of which adversely affected residents' physical and mental health. The lack of natural light and proper ventilation due to these extensions was particularly detrimental. Flores-Larsen and Filippín (2020) highlight the health risks posed by extreme heat in poorly insulated low-income social housing in Argentina. During heatwaves, indoor temperatures frequently exceeded safe limits (over 25 degrees C), leading to increased cardiovascular and respiratory issues. In a similar vein, Porras-Salazar et al. ( 2020 ) examine energy poverty in social housing schemes in central-south Chile, correlating thermal comfort levels with health outcomes. They found a direct link between poor thermal insulation and an increase in respiratory diseases, exacerbated by the use of cheaper, polluting heating methods (log burners) that families have installed to increase heat and comfort. Cáceres et al. ( 2001 ) also identify indoor air pollution in La Pintana , Santiago, as a significant health risk, with respiratory diseases linked to the use of inexpensive but polluting fuels. Torres et al. ( 2008 ) explore the quality of life of low-income elderly adults in Santiago, noting that the distance from family members and the stress of environmental violence in urban areas with high concentration of poverty, adversely affected their psychological well-being. Burgos et al. ( 2015 ) discuss child environmental health in relocated families from informal settlements to social housing in Santiago, highlighting increased respiratory diseases and safety concerns in social housing schemes. These findings underscore that neoliberal housing models, by privileging cost-efficiency (for example by providing inadequate insulation) over environmental quality, often externalise the burden of health to low-income residents, creating a feedback loop where poor housing worsens health, which then limits productivity and employment stability. Conversely and as Table 5 shows, some policies and interventions that emphasised renovation and participatory planning have been highlighted by two papers. Vergara et al. ( 2019 ) emphasise the role of third sector organisations in improving physical and social conditions in deteriorated social housing in Chile, noting improvements in self-esteem and community health. Orlando-Romero et al. ( 2023 ) study the link between social housing regeneration, quality of life, and health, demonstrating that renovations improved living conditions and residents' physical and mental health by addressing issues such as structural deterioration, mould, and lack of privacy. These cases signal the importance of ongoing public investment and community collaboration in mitigating the health-related impacts of inadequate housing. Table 5 Summary of Health Outcomes Outcome Study Country Key Finding Health Factor Negative Carrasco & O’Brien ( 2021 ) Chile Unregulated extensions worsened ventilation and lighting, increasing physical and mental health risks Overcrowding, Mental Health Flores-Larsen & Filippín (2020) Argentina Poor insulation led to heat-related illness during extreme weather Thermal stress, Cardiovascular risk Porras-Salazar et al. ( 2020 ) Chile Poor thermal comfort and wood-burning increased respiratory illnesses Energy poverty, Respiratory illness Cáceres et al. ( 2001 ) Chile Indoor air pollution from low-quality fuels linked to respiratory diseases Indoor pollution, Respiratory illness Torres et al. ( 2008 ) Chile Isolation and environmental violence impacted elderly residents’ psychological well-being Mental health, Social isolation Burgos et al. ( 2015 ) Chile Relocated families showed increases in child respiratory diseases and safety concerns Child health, Environmental risk Positive Orlando-Romero et al. ( 2023 ) Chile Renovated social housing improved physical and mental health Structural quality, Mental health Vergara et al. ( 2019 ) Chile Third sector interventions enhanced housing quality and community well-being Community health, Self-esteem Economy : Neoliberal housing programs in both countries often operate under the “assumption” that property ownership will drive socio-economic mobility. However, the economic outcomes summarised in Table 6 indicates otherwise. Two papers link the previous outcome of health and household economy. Porras-Salazar et al. ( 2020 ) highlight how limited access to heating systems and the ability to invest in energy influence the thermal comfort and health of residents, exacerbating economic and social inequality in social housing in Chile. Similarly, Flores-Larsen and Filippín (2020) further emphasise the economic constraints that limit low-income families' ability to maintain a healthy indoor environment during extreme heat events in Argentina (Flores-Larsen & Filippín, 2020, p. 41). Two other papers highlight the tension between neoliberal real estate market objectives and the social housing goals aimed at providing public benefits. Stang et al. ( 2022 ) examine the economic implications of neoliberal housing policies on migrants in Santiago and Antofagasta, Chile. They found that a deregulated real estate market combined with state subsidies led to economic difficulties for migrants, including high rents and overcrowded living conditions. Fuster-Farfán ( 2020 ) explores the dynamics of social housing in high-value areas, highlighting the economic challenges and contradictions of neoliberal capitalism that prioritise market value over social function. One paper delves into the benefits of home ownership. Gil and Celhay ( 2022 ) found that property rights in low-income housing did not lead to significant economic improvements, as expected. Formal property ownership did not result in greater housing investment or access to formal credit, except for small retail loans obtained by some families, indicating that property rights alone are insufficient to elevate the socio-economic status of low-income households. Following on the access to credit, one paper finds a positive outcome. Lehner and Gerscovich ( 2021 ) contrast housing microfinance with “social production of habitat” in Buenos Aires (i.e. community-led activities), showing that both approaches could complement each other to address household poverty. Nevertheless, the wider evidence suggest that the broader economic model continues to undervalue the social function of housing, placing vulnerable populations in structurally precarious positions with limited opportunities for upward mobility. More state support for collective approaches are needed to address housing deficits while supporting community resilience and enabling economic mobility. Table 6 Summary of Economic Outcomes Outcome Study Country Key Finding Economic Factor Negative Porras-Salazar et al. ( 2020 ) Chile Inability to afford heating created thermal stress and inequality Energy affordability Flores-Larsen & Filippín (2020) Argentina Families could not afford cooling systems during heatwaves Energy affordability Stang et al. ( 2022 ) Chile Migrants faced overcrowding due to deregulated rental markets Rent burden, Real estate exclusion Fuster-Farfán ( 2020 ) Chile Real estate pressures undermined low-income housing sustainability in high-value areas Gentrification, Economic displacement Gil & Celhay ( 2022 ) Chile Property rights did not translate into better credit or economic outcomes Credit inaccessibility, Ownership paradox Positive Lehner & Gerscovich ( 2021 ) Argentina Microfinance and collective housing models supported financial resilience Alternative finance, Community support Social Cohesion : As Table 7 summarises, the spatial and institutional design of neoliberal housing programs in both countries has had mixed effects on social cohesion, a critical factor in escaping poverty cycles. Three papers focus on the contradictions between housing market forces and community cohesion. Zunino and Hidalgo ( 2009 ) discuss how the concentration of social housing in peripheral areas of Chile limits residents' social cohesion and political participation. The allocation of social housing to these areas, driven by market forces, resulted in socio-economic isolation and weakened community bonds. Fuster-Farfán ( 2020 ) underscores the challenges of maintaining social cohesion in high-value areas like Las Condes , Santiago, where the exclusivity of these neighbourhoods created social and symbolic barriers that hindered upward social mobility, even with housing subsidies. Similarly, Fuentes and Rodríguez (2020) analyse the impact of free market policies on social inclusion and exclusion in Santiago, noting that urban segregation limits social mobility and cohesion. A further paper delves into the pitfalls of maintaining social networks after the privatisation of a former informal settlement. Carrasco and O’Brien ( 2021 ) highlight the lack of community organisation in Quinta Monroy , where housing extensions were carried out individually rather than collectively, undermining social cohesion. The evidence shows that geographical and socio-economic marginalisation has resulted in weakened community bonds, isolation, and reduced political agency. Even in affluent areas, symbolic barriers and exclusivity prevent genuine integration of low-income residents, reinforcing class stratification. On the other hand, community-led and participatory housing processes have helped foster trust, mutual aid, and social organisation, as five papers reporting on social cohesion demonstrate. Cutts and Moser ( 2015 ) analyse state-community collaborative strategies in Argentina, emphasising the success of participatory processes and community self-management in strengthening social cohesion. Rioseco et al. ( 2008 ) identify changes in social networks among elderly beneficiaries of social housing programs in Chile, with building residents experiencing an increase in relationships with non-family members. Vergara et al. ( 2019 ) emphasise the role of third sector organisations in improving social cohesion in deteriorated neighbourhoods through participatory processes and community organisation in Chile (Vergara et al., 2019 ). Torres et al. ( 2008 ) show that residents in gated developments (condominiums) in Santiago have better social relationships than those in apartment buildings, highlighting the role of social networks in quality of life. Lehner and Gerscovich ( 2021 ) contrast two housing finance programs in Argentina, showing how collective self-management can enhance social cohesion compared to individual microcredit. Thus, when housing policy integrates participation, empowerment, and social infrastructure, it holds greater potential to interrupt the cycle of poverty. Table 7 Summary of Cohesion Outcomes Outcome Study Country Key Finding Cohesion Factor Negative Zunino & Hidalgo ( 2009 ) Chile Peripheral housing limited community ties and political participation Social fragmentation Fuster-Farfán ( 2020 ) Chile Exclusivity of high-value areas inhibited integration of subsidised households Symbolic exclusion, Social fragmentation Fuentes & Rodríguez (2020) Chile Urban segregation reinforced social marginalisation Social fragmentation Carrasco & O’Brien ( 2021 ) Chile Individually driven extensions weakened collective organisation Fragmented networks Positive Cutts & Moser ( 2015 ) Argentina State-community collaboration improved social networks and solidarity Participatory governance Rioseco et al. ( 2008 ) Chile Increased social interaction among elderly residents in public housing Social integration Vergara et al. ( 2019 ) Chile Third sector participation fostered community rebuilding Participatory governance Torres et al. ( 2008 ) Chile Gated developments improved resident sociability compared to apartments Community self-management Lehner & Gerscovich ( 2021 ) Argentina Collective housing processes enhanced trust and mutual aid Community self-management Urban Space : The evidence summarised in Table 8 suggest that urban geography shaped by neoliberal housing policies reflects and reproduces inequality. Zunino and Hidalgo ( 2009 ) illustrate how market-driven housing policies resulted in the construction of large, standardised housing complexes in peripheral areas, often lacking adequate infrastructure and services, which perpetuated urban fragmentation and socio-economic polarisation. Dohnke (2015) highlights how investment patterns in Santiago de Chile favoured affluent areas, attracting middle-class developments while relegating subsidised housing to less desirable regions, thus reinforcing social segregation. In a similar vein, Fuster-Farfán ( 2020 ) highlights the difficulties of maintaining social housing in high-value areas, where regulatory flexibility and deregulated real estate markets have marginalised low-income populations. Celhay ( 2020 ) shows that informal housing arrangements can sometimes provide better location benefits and social capital compared to formal housing, despite poorer housing quality. Still, since the social housing schemes do not benefit from this results, the paper is recorded as negative in Table 8 . Inzulza and Cárdenas ( 2017 ) discuss the impact of post-earthquake social housing reconstruction in Talca, Chile, where displaced residents were relocated to peripheral areas, disrupting established social fabrics and leading to socio-economic isolation. Such spatial fragmentation reinforces social exclusion and limits employment opportunities, a key mechanism in the perpetuation of poverty. Notably and as shown here, informal housing, despite its precarious conditions, sometimes offers better location advantages and social networks than formal social housing. This challenges the neoliberal emphasis on formalisation and suggests that location, infrastructure, and community integration are equally, if not more, important than legal tenure. Table 8 Summary of Spatial Outcomes Outcome Study Country Key Finding Urban Spatial Factor Negative Zunino & Hidalgo ( 2009 ) Chile Peripheral, standardised complexes led to socio-economic polarisation Urban segregation, Peripheralisation Dohnke (2015) Chile Investment prioritised affluent zones, marginalising low-income areas Urban segregation, Peripheralisation Fuster-Farfán ( 2020 ) Chile Market-driven planning failed to secure long-term urban integration for low-income residents Urban segregation, Peripheralisation Celhay ( 2020 ) Chile Informal settlements sometimes offered better social and locational benefits than formal housing Functional informality Inzulza & Cárdenas ( 2017 ) Chile Earthquake recovery policies relocated families away from original communities Displacement, Loss of social capital In summary, the above thematic review shows that structural conditions such as a neoliberal housing regime define policy outcomes. The evidence from Argentina and Chile indicates that the benefits of neoliberal housing policies are highly uneven and deeply conditioned by structural, economic, and spatial inequalities. Health, economic opportunities, social cohesion, and urban inclusion are not guaranteed by access to housing alone, especially when delivery models emphasise market logic over social equity. Policies that reinforce individual responsibility, deregulation, and formal ownership, hallmarks of the neoliberal model, frequently fail to disrupt the cycle of poverty and can even exacerbate it. In contrast, participatory, flexible, and community-rooted approaches, supported by strong regulatory frameworks and public investment, show greater promise in creating sustainable housing outcomes that empower low-income populations. Future housing strategies must therefore transcend market-driven paradigms and embrace holistic frameworks that prioritise human well-being, environmental quality, and spatial justice, breaking the links between inadequate housing and intergenerational poverty. Risk of bias results: Reflections on Assessing Mixed-Methods Research in a Systematic Review Assessing the risk of bias in a systematic review that incorporates quantitative, qualitative, and mixed-methods studies presents a unique set of methodological and interpretive challenges. Recognising the epistemological diversity within the literature on neoliberal housing policies in Argentina and Chile, this review adopted a bespoke scoring system to ensure consistency, transparency, and fairness in the evaluation process. While this approach allowed for a nuanced comparison across disparate research designs, the results of the assessment also reveal key limitations in the existing literature and illustrate broader tensions in applying quality appraisal tools across methodological paradigms. Additional file 4 shows the final risk of bias assessment and scoring. None of the papers reviewed achieved the maximum weighted score of 1.25 points awarded to a hypothetical model paper that had an adequate sample size considering its methodological approach (1 point), appropriate study design (1 point), and data collection (1 point), as well as reporting all potential confounding factors (6 points). The highest scoring paper was Celhay ( 2020 ) with 1.18 points, with a deduction for not reporting pre-existing health conditions in a study of 32 subsidised housing projects in Santiago, Chile. Although the aim of the paper was to compare household preferences between living in informal housing versus government-led subsidised housing, the exclusion of pre-existing health conditions poses a small risk to the results, as some households might prefer a location due to its proximity to health centres or other formal/informal care provisions. The next highest scoring paper is Burgos (2015) with 1.13 points. This paper reviews children’s health in government-led subsidised housing, finding positive effects compared to children in households living in slums. However, it only reports on two confounding factors: household income and housing conditions. The crucial factor of pre-existing health conditions is merely mentioned, as are other factors like education and crime rates. Other papers scoring above 1 (Flores Larsen 2021, 1 point; Lehner 2021 , 1.05; Gill, 20twenty-two, 1.05; and Torres et al 2008 , 1.10) all have similar issues of not reporting or not mentioning a confounding factor. The remaining papers that scored below 1 all failed to report a sample size (Cutts, 2015 ; Flores-Larsen 2021 ; Vergara 2019; Orlando-Romero, 2023; Porras-Salazar, 2020; Perez, 2017; Dohnke, 2015; Ozler, 2012 ; Perez, 2018 ; Cáceres et al, 2001 ; Stang et al. 2022 ; Zunino and Hidalgo, 2009 ; Fuster-Farfán 2020 ; and Fuentes and Rodriguez, 2020 ). The lowest scoring paper is Inzunza and Cárdenas (2017), which fails to report sample size and also has an inadequate study design. The shortcomings of the paper include the lack of diversity in the interviews (only 18 residents of the 238,817 reported in the paper that were affected by the earthquake). The team considered that the study needed a higher representative sample or a more diverse base of interviewees, such as including local authorities and NGOs operating after the earthquake, which could have provided a higher-level perspective of the entire neighbourhood. This example highlights how even methodologically valid qualitative work can falter when critical perspectives or sample representativeness are missing. The results underscores a broader issue: while many studies provide strong contextual or theoretical contributions, they often lack systematic reporting of confounding variables, limiting the generalisability of their findings. This reflects a broader trend in the literature: while there is an emphasis on policy-level analysis or structural critique, fewer studies engage in multi-variable, intersectional analysis that would clarify how various socio-economic conditions mediate the effects of housing policy. Given the complex realities of poverty, especially as it relates to housing, health, and employment, this omission weakens causal inferences and hampers policy translation. One of the most complex areas of risk assessment involved sample size. Recognising that qualitative research does not adhere to statistical generalisability in the same way as quantitative studies, the team assigned a lower weighting (15%) to this criterion. However, the fact remains that many studies failed to report sample size altogether, including several with rich empirical insights (for example Vergara 2019 and Orlando-Romero 2023). This lack of transparency, whether in interview-based, ethnographic, or survey research, limits the replicability and evaluative clarity of these works, and suggests the need for improved minimum reporting standards, regardless of study design. In sum, the application of a weighted, variable-based risk of bias assessment allowed this systematic review to maintain consistency across a methodologically diverse evidence base. However, the process also exposed significant limitations in the current literature, notably, inconsistent reporting of sample sizes and confounding variables, and varied attention to study design integrity. Ultimately, the difficulty of assessing mixed-methods studies lies not in their inclusion but in their standardised evaluation. While tools such as the one developed for this review represent a step forward, future systematic reviews should consider even more flexible frameworks that are attuned to the epistemological logics of each methodology, while still demanding transparency, accountability, and rigour. This exercise suggests that improving reporting practices, particularly for sample size, confounding variables, and data triangulation, would substantially raise the evaluative quality of policy-relevant research in this field. At the same time, risk of bias tools must continue to evolve to avoid penalising valid forms of qualitative inquiry that enrich our understanding of housing, poverty, and inequality in complex urban contexts. While our bespoke tool enabled consistent appraisal across diverse study types, its lack of formal external validation and the variability in reporting quality across studies represent important limitations that may affect the precision of comparative assessments. Conclusions This systematic review demonstrates that the outcomes of neoliberal housing policies for low-income families in Argentina and Chile are shaped by a complex interplay of structural, spatial, and institutional factors. The findings reveal that while housing provision under neoliberal regimes has succeeded in expanding homeownership and formalising tenure for many households, the benefits of these policies remain highly uneven and often insufficient to break the cycle of poverty. Across the thematic domains of health, economic security, social cohesion, and urban space, the review shows that market-driven housing strategies frequently externalise risk to residents, particularly in environments where regulatory oversight, social infrastructure, and public investment are weak or unevenly distributed. Poor-quality housing, inadequate insulation, and spatial segregation have direct and indirect consequences on residents’ physical and mental health, limiting their capacity to engage in stable employment and undermining long-term economic resilience. Moreover, the promise of economic uplift through property ownership has largely failed to materialise for most beneficiaries of social housing. While formal tenure provides legal security, it rarely leads to enhanced access to credit or asset accumulation in contexts of economic precarity. In many cases, households remain locked into substandard or peripheral housing, disconnected from employment hubs and public services. Conversely, contextual and institutional variables, such as strong community organisation, participatory governance, and strategic location, can mitigate some of the adverse effects of neoliberal housing policies. Programs rooted in collaborative planning, community-led housing production, and the active involvement of third-sector organisations are associated with more positive outcomes across all thematic domains, particularly where they emphasise social cohesion, inclusion, and wellbeing alongside physical infrastructure. From a methodological standpoint, the review also highlights the limitations of current research practices, including inconsistent reporting of key variables and a lack of intersectional analysis. The bespoke risk of bias assessment confirms that while many studies offer valuable insights, there is a need for greater methodological transparency and standardisation, particularly concerning sample size reporting and the treatment of confounding variables. In sum, the benefits of neoliberal housing policies are not determined solely by access to housing but by how housing is situated within a broader ecology of social policy, infrastructure, and equity. To ensure housing functions as a tool for poverty alleviation, policy frameworks must move beyond market logic and adopt integrated, equity-focused approaches that prioritise health, social cohesion, urban connectivity, and long-term economic sustainability. Future research should aim to fill geographical and methodological gaps, particularly in the underrepresented Argentinean and regional context, and should further investigate the roles of governance, institutional design, and community agency in shaping housing outcomes. Future systematic reviews in LMIC policy contexts should prioritise the development of adaptable, mixed-methods appraisal tools and context-sensitive synthesis frameworks that account for the complexity, data variability, and epistemological diversity characteristic of research in these settings. Only through such holistic and critical engagement can we advance towards housing systems that serve as engines of social inclusion rather than mechanisms of marginalisation. Declarations The authors are grateful for the funding and support provided by the Reading Real Estate Foundation; Fondecyt 11200793 ANID, Chile and Fondecyt ANID-SIA 85240235, Chile. The authors declare that they have no competing interests. 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Urban Geography , 30 (5), 514-542. https://doi.org/10.2747/0272-3638.30.5.514 Supplementary Files Additionalfile1.docx Additionalfile2.docx Additionalfile3.docx Additionalfile4.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 07 Apr, 2026 Reviewers agreed at journal 26 Jan, 2026 Reviewers invited by journal 06 Oct, 2025 Editor assigned by journal 22 Sep, 2025 First submitted to journal 24 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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07:00:50","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":16660,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7196007/v1/0b1e85e97afc3b3d97500e97.docx"},{"id":93747293,"identity":"92deb830-ff14-4eab-b6a9-e7f7f76efd35","added_by":"auto","created_at":"2025-10-17 07:00:50","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":17833,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile4.docx","url":"https://assets-eu.researchsquare.com/files/rs-7196007/v1/15298adfc7acce647d1317d2.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eNeoliberal Housing and the Health-Poverty Nexus: Mapping of Evidence using a Systematic Framework Synthesis from Argentina and Chile\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSystematic reviews from high-income countries consistently demonstrate that stable, affordable, and quality housing is associated with improved mental and physical health outcomes for low-income populations. For example, Braveman et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) found that affordable housing reduces psychological stress and supports better overall health, particularly among families at risk of homelessness. Similarly, housing interventions such as homeless shelters have been shown to significantly reduce anxiety, depression, and substance abuse disorders in homeless individuals (Rog et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Improvements in housing conditions, such as better ventilation, lead removal, and insulation, are also associated with reductions in respiratory diseases like asthma (Krieger \u0026amp; Higgins, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Thomson et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSystematic reviews that include studies from Low and Middle Income Countries (LMIC) reveal that poor housing conditions pose severe health risks, particularly in the form of infectious diseases such as tuberculosis, cholera, and malaria (Vlahov et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For instance, a review by Lilford et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) highlights that housing interventions in slum areas, such as upgrading sanitation infrastructure and improving access to clean water, can reduce the prevalence of diarrheal diseases and other waterborne illnesses, which are a leading cause of mortality in these regions. Moreover, systematic reviews emphasise that interventions focusing on housing affordability and security are crucial for improving mental health in LMICs. Indeed, a study by Weimann and Oni (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that lack of secure tenure in informal settlements is linked to increased levels of stress and anxiety, as residents live under constant threat of eviction. In such contexts, housing security policies, including land tenure reforms and slum upgrading projects, have been shown to alleviate some of the psychological burdens associated with housing instability (Baker et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the growing recognition of the links between housing and health and the perpetuation of the poverty cycle, the above research lacks understanding of the structural implications of neoliberal housing policies. Most studies fail to critically engage with the broader economic and political frameworks brought by neoliberalism in housing such as the retreat of the state from housing provision that has deepened the structural inequities that affect health outcomes (Satterthwaite et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For instance, and as shown this far, while there is substantial evidence linking poor housing conditions with adverse health outcomes in LMIC, there is limited research on how neoliberal housing policies, such as the reliance on private-sector for housing solutions, might affect housing instability and health inequities. Furthermore, the market-oriented approach of neoliberal policies tends to overlook the broader social and health needs of low-income populations, focusing instead on housing as an economic commodity rather than as a human right or a public health imperative. In countries like Chile, this shift has left many low-income families with a new problem of families owning a house but still in poverty (Rodriguez and Sugranyes, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotwithstanding, there are contextual factors that might mitigate the impact of neoliberal policies. For example community cohesion and social ties can help low-income families navigate housing insecurity, access informal economies, and pool resources to maintain housing stability. Research has shown that in tightly knit communities, residents are more likely to engage in collective action to prevent evictions, advocate for housing rights, or secure basic services such as water and sanitation (Mitlin, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Such initiatives help to soften the negative impacts of neoliberal policies, reducing housing insecurity and improving health outcomes by providing more stable living conditions and a sense of security. Likewise, the degree of urban connectivity and access to job opportunities is another critical factor. Neoliberal housing policies in LMICs mostly support home ownership via the provision of subsidies, benefits that can only be accessed via a demonstrable and steady income (Murray and Clapham, 2015). Access to employment is therefore crucial for maintaining housing stability. Research in Latin American cities like São Paulo and Mexico City shows that low-income families in better-connected neighbourhoods are more likely to experience upward mobility and improved living conditions despite facing high housing costs (Caldeira, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Schteingart \u0026amp; Salazar, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These contextual factors, community cohesion and urban connectivity, highlight the importance of considering local social dynamics and infrastructure in the systematic review approaches. As Baker and Mason (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) argue, without an understanding of these broader policy dynamics, efforts to improve health outcomes through housing interventions may be piecemeal and unsustainable.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReview Objective\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eFilling this research gap requires moving beyond a narrow focus on individual housing interventions to examine the broader structural impacts of neoliberal housing reforms on household health and poverty. In this review, the nexus centres around the cycle of poverty that affordable housing policies aim to solve: People who live in poverty often struggle to afford safe and suitable housing. They may live in overcrowded, unsafe, or unsanitary conditions, which can lead to a variety of health problems. In addition, inadequate housing can make it more difficult for people to find and maintain employment, which can perpetuate the cycle of poverty (several authors describe the housing-health and poverty nexus, for developed economies see Kemp, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e and Dewilde, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e. For LMIC see Davis, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e and Zadeh et al, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This calls for a more holistic methodological approach that centring on the intersection of housing and health in the cycle of poverty, looks at the contextual factors that might mitigate the impact of neoliberal housing policies, such as connectivity to jobs and community cohesion. Acknowledging this research gap, this systemic review therefore asks: \u003cem\u003eWhat factors explain increasing/decreasing benefits of neoliberal housing policies amongst low income families in Argentina and Chile?\u003c/em\u003e\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eFramework synthesis is a method used in systematic reviews to integrate existing qualitative research by mapping data onto an a priori framework, often based on theories or concepts from previous research (Brunton et al, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As the authors explain, the approach involves first identifying key categories in the framework which provides a ‘scaffold’ against which the data is organised. Then coding and categorising data from included studies to fit these categories.\u003c/p\u003e\u003cp\u003eFor the purpose of our study, the team developed an a priori thematic framework, informed by both theoretical constructs (e.g., health-poverty nexus, urban inequality) and preliminary scoping of the literature. In alignment with the PRISMA 2020 guidelines for systematic reviews and the PRISMA Extension for Scoping Reviews (PRISMA-ScR), the adopted method preserves the core principles of systematic synthesis, transparency, replicability, and methodological rigour, while allowing for conceptual flexibility appropriate to complex, interdisciplinary evidence bases. The framework functioned as a coding scaffold, enabling structured comparison across diverse study types and thematic domains (health, economy, cohesion, and urban space), consistent with guidance for qualitative and mixed-methods integration in systematic reviews (Harden \u0026amp; Thomas, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Thomas \u0026amp; Harden, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThematic framework\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eThemes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEquality\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInequality\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEconomic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCohesion/sociability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIsolation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommunity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntegration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSprawl/gentrification\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban Space\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eDomain being studied: (identifying key concepts)\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe primary focus of this paper is to thematically and systematically evaluate the factors identified by the literature that explain increasing/decreasing benefits of neoliberal housing policies amongst low income families in Argentina and Chile since the start of their respective neoliberal housing regimes. There are several frameworks to identify key concepts with the most popular one being the Population, Intervention, Comparison, Outcome (PICO) framework used in health studies. In order to cover for the geographical component of our review, we have adapted the framework to Population, Intervention, Setting and Outcomes (PISO). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below presents the framework adopted for this review.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFramework for key concept identification\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePOPULATION\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow income families in Argentina and Chile\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINTERVENTION\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeoliberalism\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSETTING\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial housing schemes in cities (defined as urban agglomerations of more than 250,000 inhabitants)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOUTCOME\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEconomic/health equality; community cohesion and urban integration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cem\u003eSearch terms and strategy\u003c/em\u003e:\u003c/p\u003e\u003cp\u003eThe search terms were compiled by two methods: generating terms based on meaning (using synonyms or closely related concepts) and by grammar (plurals), by style (acronyms, abbreviations, professional jargon). The team also gathered terms from publications retrieved during the testing of the methodology, collecting key words assigned to articles. The team also added controlled vocabulary adapted from each database that was mined. Additional file 1 compiles all search terms used by the team.\u003c/p\u003e\u003cp\u003eThe team mined the following repositories: Scopus, WebofScience and PubMed in English and Spanish. Dates were limited to the time when neoliberal housing regimes were implemented in both countries (1990) to publications available until December 2023. For a more comprehensive search the team used a text word search (title, abstract and any other part of the text). Additional file 2 shows the search strategies implemented in all repositories.\u003c/p\u003e\u003cp\u003e\u003cem\u003eTypes of studies included\u003c/em\u003e:\u003c/p\u003e\u003cp\u003eThe review includes descriptive impact studies examining factors explaining increasing/decreasing benefits of neoliberal housing policies using quantitative, qualitative or mixed-methods. Thus reflecting the multi-dimensional nature of housing policy impacts.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData extraction and data synthesis strategy\u003c/em\u003e:\u003c/p\u003e\u003cp\u003eThe team used the EPPI reviewer software to facilitate article screening, appraisal and data extraction, using EPPI’s collaborative cloud platform. After importing the searches, duplicates were automatically removed (i.e. same publication found in different databases) with a manual check by the entire team to minimise software/human error. Articles were then distributed to all four team members, to be screened by title and abstract using the pre-established protocol. Each article was screened by at least two team members, if there were disagreements, a third team member reviewed the data and agreed on its inclusion/exclusion. The full text of selected articles was then read to determine inclusion in the final thematic synthesis. The team held an online workshop to collectively agree on final decision of all excluded articles.\u003c/p\u003e\u003cp\u003eAt this point, the team collected data for the PRSIMA report, ensuring that exclusions were justified and all articles accounted for.\u003c/p\u003e\u003cp\u003eGraphic 1: PRISMA Report\u003c/p\u003e\u003cp\u003eA data extraction spreadsheet was used at this stage covering citation details, population, geographical coverage, study purpose and aims, research methods used including data collection and analytical approach, detail of themes, outcomes and relevant quotations findings (if any) in relation to the outcomes, conclusions and limitations. The textual analysis of final selection of papers followed line by line coding (Harden and Thomas, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) for their categorisation in the pre-established thematic framework (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The content of these themes was then synthesised trying to keep as close as possible to the original text used by the authors and considering the emerging factors reported by the authors that explain increasing/decreasing benefits of neoliberal housing policies.\u003c/p\u003e\u003cp\u003e\u003cem\u003eRisk of bias\u003c/em\u003e:\u003c/p\u003e\u003cp\u003eThe critical appraisal checklist is a widely used method by researchers conducting systematic reviews (Tod et al \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This includes tools such as the Critical Appraisal Skills Programme (CASP), the Consolidated Criteria for Reporting Qualitative Research (COREQ) tool, and the Standards for Reporting Qualitative Research (SRQR) tool. Given the inclusion of quantitative, qualitative, and mixed-methods studies, we developed a bespoke risk of bias tool adapted from existing validated frameworks. Each domain in our tool was justified based on relevance to the methodological diversity of the included studies and tailored to assess key quality criteria, such as study design appropriateness, data collection rigour, sample transparency, and reporting of confounding variables. To ensure internal consistency and usability, the tool was piloted on a subset of five diverse studies representing different methodological types (qualitative, quantitative, mixed). Based on this pilot, minor refinements were made to scoring instructions and domain definitions. This piloting process functioned as a form of face and content validation, appropriate for context-specific appraisal tools in reviews of complex social interventions (Harden \u0026amp; Thomas, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Tod et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While the tool is not externally validated, its transparent development process and clear scoring logic ensured consistent application across all included studies, supported by reviewer consensus procedures. Additional file 3 lists all variables and their justification for inclusion as well as the resulting risk of bias assessment template used by the team. During implementation, each article was assessed by two team members, awarding a score of 1 for each appropriately addressed variable and 0 when not. A subsequent online workshop was held to agree on final scores and determine the weighting for each risk of bias criterion. Given the diversity of study types, the weighting for sample size was set at 15%, allowing fair consideration of purely qualitative studies that used small samples but conducted in-depth interviews with a variety of stakeholders (i.e., from government level to homeowners). Study design was weighted at 50%, allowing nuanced consideration of the different study types and research questions presented by all authors. Similarly, data collection was weighted at 30%, while confounding factors had a collective weighting of 5% (i.e., Household Income/Employability, Pre-existing Health Conditions, Educational Level, Urban Infrastructure/Access to Services, High Crime Rates, Housing Market Conditions), each awarded one point when reported and half point if only mentioned but not reported, with the resulting sum weighted by 5%.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cem\u003eMapping the Scope and Biases of the Existing Literature\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe analysis of the twenty-two studies included in this systematic review reveals important insights into both the scope and limitations of existing research in Argentina and Chile. By mapping the key characteristics of these studies, such as geographic distribution, settlement demographics, and methodological choices, this section highlights and discusses both the areas of scholarly concentration and notable gaps in the literature.\u003c/p\u003e\u003cp\u003eOf the entire dataset, nineteen settlements (86% of total) are located in Chile, and three settlements (14%) are in Argentina (See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below). A significant geographical imbalance is immediately apparent with the vast majority of studies concentrated Chile and in the Santiago Metropolitan Region. This alone accounts for 60% of the Chilean cases, while the rest are dispersed across Valpara\u0026iacute;so, Concepci\u0026oacute;n, and Tarapac\u0026aacute;. In contrast, the only three cases in Argentina are all in different locations, spanning Buenos Aires, La Pampa, and Santa Fe. This skewed distribution suggests a strong academic emphasis on the Chilean experience with neoliberal housing policies, potentially driven by the country's pioneering role in adopting neoliberal reforms in Latin America in the late 1980\u0026rsquo;s (Murray and Clapham, 2015). However, it also underscores a substantial research gap in the Argentine context, limiting the ability to conduct broader comparative analyses across diverse national frameworks and limiting generalisability.\u003c/p\u003e\u003cp\u003eIn terms of settlement scale, the majority of studies (59%) examine communities with over 500 residents, while 34% focus on smaller housing schemes ranging between 101 and 500 residents. Only two papers focus at the housing scheme level of less than 100 residents (see Scale column in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This differentiation may reflect divergent housing challenges in urban versus peri-urban areas, but it also raises questions about the generalisability of the findings across different spatial and demographic contexts.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMapping of dataset results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublication ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArea covered\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eScale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBaeza et al., (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeighbourhood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago \u0026amp; Valparaiso\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurgos (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommune\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTarapac\u0026aacute;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u0026aacute;ceres et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommune\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarrasco (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTarapac\u0026aacute;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCelhay (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCutts (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSanta Fe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDohnke (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlores-Larsen (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLa Pampa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuentes y Rodriguez (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGill (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInzunza y C\u0026aacute;rdenas (2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeighbourhood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMaule\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLehner (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBuenos Aires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrlando-Romero (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeighbourhood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eValpara\u0026iacute;so\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOzler (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNeighbourhood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerez (2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommune\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerez (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePorras-Salazar (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConcepcion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRioseco (2008)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStang et al., (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago \u0026amp; Antofagasta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTorres et al., (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommune\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101\u0026ndash;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVergara (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHousing scheme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSantiago\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZunino, Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;100\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eValparaiso\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegarding methodology, twelve of the twenty-two analysed articles rely purely on qualitative data with only 4 using quantitative whilst 6 use mixed methods (See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Qualitative depth appears to be pursued primarily through interviews complemented with other forms of data collection including household or neighbourhood surveys using field work observations. From all the studies using interviews, only six of them provide data on both the number of people interviewed and the total population of the study, making it challenging to assess the proportion of the population represented in the sample. Still, all six articles report that more than 75% of the population was interviewed. However, the absence of standardised reporting protocols across studies hinders efforts to assess the validity and representativeness of these research findings.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMapping of research methods and risk of bias score\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePublication ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMethod\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimary data\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSecondary data\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurgos (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePopulation surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u0026aacute;ceres et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePopulation surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarrasco (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and physical survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCelhay (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and population surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCutts (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and physical survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDohnke (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003en/a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelevant housing market data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlores-Larsen (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ehousehold survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelevant indexes and benchmarks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuentes y Rodriguez (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN/a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCensus (CASEN)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGill (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and population survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInzunza y C\u0026aacute;rdenas (2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpatial data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLehner (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLegal docs and construction reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrlando-Romero (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and focus groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOzler (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and physical survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerez (2017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and physical survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerez (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews and physical survey\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSpatial data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePorras-Salazar (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuantitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePopulation surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelevant meteorological data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRioseco (2008)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePopulation surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStang et al., (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTorres et al., (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePopulation surveys\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelevant statistics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVergara et al (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQualitative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGovernment documents and reports\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZunino, Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterviews\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCensus and spatial data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAltogether, the review reveals a literature that is rich in case studies, particularly in Chilean urban contexts, but constrained by geographic and methodological concentration. The predominance of Santiago-based studies, along with a reliance on select methodological tools and inconsistent reporting, suggests the need for broader, more diversified research efforts. Addressing these gaps could involve targeted studies in underrepresented regions, increased attention to smaller and non-urban settlements, and the adoption of more rigorous standards for data collection and reporting. Such measures are essential for advancing a more comprehensive and comparative understanding of how neoliberal housing policies are reshaping urban and peri-urban life in both countries.\u003c/p\u003e\u003cp\u003e\u003cem\u003eNarrative synthesis\u003c/em\u003e:\u003c/p\u003e\u003cp\u003eFollowing the thematic framework for this paper (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), this section now presents the results of the increasing/decreasing benefits of neoliberal housing policies in Chile and Argentina. All papers included in this section reported on the specific outcomes of a social housing scheme delivered under neoliberal policies, with the reported outcomes divided into: health, economy, social cohesion, and urban space.\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eHealth\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eThe results summarised in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e show that one of the most persistent negative outcomes of neoliberal housing policies lies in their detrimental health impacts, which, in turn, deepen poverty cycles. Carrasco and O\u0026rsquo;Brien (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explore the long-term health impacts of incremental social housing schemes in \u003cem\u003eQuinta Monroy, Iquique\u003c/em\u003e, Chile. They found that unregulated housing extensions led to a deterioration in living conditions, including poor ventilation and lighting, overcrowding, and increased safety risks, all of which adversely affected residents' physical and mental health. The lack of natural light and proper ventilation due to these extensions was particularly detrimental. Flores-Larsen and Filipp\u0026iacute;n (2020) highlight the health risks posed by extreme heat in poorly insulated low-income social housing in Argentina. During heatwaves, indoor temperatures frequently exceeded safe limits (over 25 degrees C), leading to increased cardiovascular and respiratory issues. In a similar vein, Porras-Salazar et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) examine energy poverty in social housing schemes in central-south Chile, correlating thermal comfort levels with health outcomes. They found a direct link between poor thermal insulation and an increase in respiratory diseases, exacerbated by the use of cheaper, polluting heating methods (log burners) that families have installed to increase heat and comfort. C\u0026aacute;ceres et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) also identify indoor air pollution in \u003cem\u003eLa Pintana\u003c/em\u003e, Santiago, as a significant health risk, with respiratory diseases linked to the use of inexpensive but polluting fuels. Torres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) explore the quality of life of low-income elderly adults in Santiago, noting that the distance from family members and the stress of environmental violence in urban areas with high concentration of poverty, adversely affected their psychological well-being. Burgos et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) discuss child environmental health in relocated families from informal settlements to social housing in Santiago, highlighting increased respiratory diseases and safety concerns in social housing schemes.\u003c/p\u003e\u003cp\u003eThese findings underscore that neoliberal housing models, by privileging cost-efficiency (for example by providing inadequate insulation) over environmental quality, often externalise the burden of health to low-income residents, creating a feedback loop where poor housing worsens health, which then limits productivity and employment stability.\u003c/p\u003e\u003cp\u003eConversely and as Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows, some policies and interventions that emphasised renovation and participatory planning have been highlighted by two papers. Vergara et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) emphasise the role of third sector organisations in improving physical and social conditions in deteriorated social housing in Chile, noting improvements in self-esteem and community health. Orlando-Romero et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) study the link between social housing regeneration, quality of life, and health, demonstrating that renovations improved living conditions and residents' physical and mental health by addressing issues such as structural deterioration, mould, and lack of privacy. These cases signal the importance of ongoing public investment and community collaboration in mitigating the health-related impacts of inadequate housing.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Health Outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey Finding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHealth Factor\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarrasco \u0026amp; O\u0026rsquo;Brien (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnregulated extensions worsened ventilation and lighting, increasing physical and mental health risks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOvercrowding, Mental Health\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFlores-Larsen \u0026amp; Filipp\u0026iacute;n (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePoor insulation led to heat-related illness during extreme weather\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eThermal stress, Cardiovascular risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePorras-Salazar et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePoor thermal comfort and wood-burning increased respiratory illnesses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEnergy poverty, Respiratory illness\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026aacute;ceres et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndoor air pollution from low-quality fuels linked to respiratory diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIndoor pollution, Respiratory illness\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTorres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIsolation and environmental violence impacted elderly residents\u0026rsquo; psychological well-being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMental health, Social isolation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBurgos et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelocated families showed increases in child respiratory diseases and safety concerns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChild health, Environmental risk\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrlando-Romero et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRenovated social housing improved physical and mental health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStructural quality, Mental health\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVergara et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThird sector interventions enhanced housing quality and community well-being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCommunity health, Self-esteem\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEconomy\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eNeoliberal housing programs in both countries often operate under the \u0026ldquo;assumption\u0026rdquo; that property ownership will drive socio-economic mobility. However, the economic outcomes summarised in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e indicates otherwise. Two papers link the previous outcome of health and household economy. Porras-Salazar et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlight how limited access to heating systems and the ability to invest in energy influence the thermal comfort and health of residents, exacerbating economic and social inequality in social housing in Chile. Similarly, Flores-Larsen and Filipp\u0026iacute;n (2020) further emphasise the economic constraints that limit low-income families' ability to maintain a healthy indoor environment during extreme heat events in Argentina (Flores-Larsen \u0026amp; Filipp\u0026iacute;n, 2020, p. 41).\u003c/p\u003e\u003cp\u003eTwo other papers highlight the tension between neoliberal real estate market objectives and the social housing goals aimed at providing public benefits. Stang et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) examine the economic implications of neoliberal housing policies on migrants in Santiago and Antofagasta, Chile. They found that a deregulated real estate market combined with state subsidies led to economic difficulties for migrants, including high rents and overcrowded living conditions. Fuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) explores the dynamics of social housing in high-value areas, highlighting the economic challenges and contradictions of neoliberal capitalism that prioritise market value over social function.\u003c/p\u003e\u003cp\u003eOne paper delves into the benefits of home ownership. Gil and Celhay (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that property rights in low-income housing did not lead to significant economic improvements, as expected. Formal property ownership did not result in greater housing investment or access to formal credit, except for small retail loans obtained by some families, indicating that property rights alone are insufficient to elevate the socio-economic status of low-income households. Following on the access to credit, one paper finds a positive outcome. Lehner and Gerscovich (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) contrast housing microfinance with \u0026ldquo;social production of habitat\u0026rdquo; in Buenos Aires (i.e. community-led activities), showing that both approaches could complement each other to address household poverty.\u003c/p\u003e\u003cp\u003eNevertheless, the wider evidence suggest that the broader economic model continues to undervalue the social function of housing, placing vulnerable populations in structurally precarious positions with limited opportunities for upward mobility. More state support for collective approaches are needed to address housing deficits while supporting community resilience and enabling economic mobility.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Economic Outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey Finding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEconomic Factor\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePorras-Salazar et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInability to afford heating created thermal stress and inequality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEnergy affordability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFlores-Larsen \u0026amp; Filipp\u0026iacute;n (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFamilies could not afford cooling systems during heatwaves\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEnergy affordability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStang et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMigrants faced overcrowding due to deregulated rental markets\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRent burden, Real estate exclusion\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReal estate pressures undermined low-income housing sustainability in high-value areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGentrification, Economic displacement\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGil \u0026amp; Celhay (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProperty rights did not translate into better credit or economic outcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCredit inaccessibility, Ownership paradox\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLehner \u0026amp; Gerscovich (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMicrofinance and collective housing models supported financial resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAlternative finance, Community support\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSocial Cohesion\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eAs Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarises, the spatial and institutional design of neoliberal housing programs in both countries has had mixed effects on social cohesion, a critical factor in escaping poverty cycles. Three papers focus on the contradictions between housing market forces and community cohesion. Zunino and Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) discuss how the concentration of social housing in peripheral areas of Chile limits residents' social cohesion and political participation. The allocation of social housing to these areas, driven by market forces, resulted in socio-economic isolation and weakened community bonds. Fuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) underscores the challenges of maintaining social cohesion in high-value areas like \u003cem\u003eLas Condes\u003c/em\u003e, Santiago, where the exclusivity of these neighbourhoods created social and symbolic barriers that hindered upward social mobility, even with housing subsidies. Similarly, Fuentes and Rodr\u0026iacute;guez (2020) analyse the impact of free market policies on social inclusion and exclusion in Santiago, noting that urban segregation limits social mobility and cohesion. A further paper delves into the pitfalls of maintaining social networks after the privatisation of a former informal settlement. Carrasco and O\u0026rsquo;Brien (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) highlight the lack of community organisation in \u003cem\u003eQuinta Monroy\u003c/em\u003e, where housing extensions were carried out individually rather than collectively, undermining social cohesion. The evidence shows that geographical and socio-economic marginalisation has resulted in weakened community bonds, isolation, and reduced political agency. Even in affluent areas, symbolic barriers and exclusivity prevent genuine integration of low-income residents, reinforcing class stratification.\u003c/p\u003e\u003cp\u003eOn the other hand, community-led and participatory housing processes have helped foster trust, mutual aid, and social organisation, as five papers reporting on social cohesion demonstrate. Cutts and Moser (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) analyse state-community collaborative strategies in Argentina, emphasising the success of participatory processes and community self-management in strengthening social cohesion. Rioseco et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) identify changes in social networks among elderly beneficiaries of social housing programs in Chile, with building residents experiencing an increase in relationships with non-family members. Vergara et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) emphasise the role of third sector organisations in improving social cohesion in deteriorated neighbourhoods through participatory processes and community organisation in Chile (Vergara et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Torres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) show that residents in gated developments (condominiums) in Santiago have better social relationships than those in apartment buildings, highlighting the role of social networks in quality of life. Lehner and Gerscovich (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) contrast two housing finance programs in Argentina, showing how collective self-management can enhance social cohesion compared to individual microcredit. Thus, when housing policy integrates participation, empowerment, and social infrastructure, it holds greater potential to interrupt the cycle of poverty.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Cohesion Outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey Finding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCohesion Factor\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZunino \u0026amp; Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePeripheral housing limited community ties and political participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSocial fragmentation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExclusivity of high-value areas inhibited integration of subsidised households\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSymbolic exclusion, Social fragmentation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFuentes \u0026amp; Rodr\u0026iacute;guez (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUrban segregation reinforced social marginalisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSocial fragmentation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarrasco \u0026amp; O\u0026rsquo;Brien (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndividually driven extensions weakened collective organisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFragmented networks\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCutts \u0026amp; Moser (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eState-community collaboration improved social networks and solidarity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eParticipatory governance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRioseco et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIncreased social interaction among elderly residents in public housing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSocial integration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVergara et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThird sector participation fostered community rebuilding\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eParticipatory governance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTorres et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGated developments improved resident sociability compared to apartments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCommunity self-management\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLehner \u0026amp; Gerscovich (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eArgentina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCollective housing processes enhanced trust and mutual aid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCommunity self-management\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eUrban Space\u003c/span\u003e:\u003c/p\u003e\u003cp\u003eThe evidence summarised in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e suggest that urban geography shaped by neoliberal housing policies reflects and reproduces inequality. Zunino and Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) illustrate how market-driven housing policies resulted in the construction of large, standardised housing complexes in peripheral areas, often lacking adequate infrastructure and services, which perpetuated urban fragmentation and socio-economic polarisation. Dohnke (2015) highlights how investment patterns in Santiago de Chile favoured affluent areas, attracting middle-class developments while relegating subsidised housing to less desirable regions, thus reinforcing social segregation. In a similar vein, Fuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) highlights the difficulties of maintaining social housing in high-value areas, where regulatory flexibility and deregulated real estate markets have marginalised low-income populations. Celhay (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) shows that informal housing arrangements can sometimes provide better location benefits and social capital compared to formal housing, despite poorer housing quality. Still, since the social housing schemes do not benefit from this results, the paper is recorded as negative in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Inzulza and C\u0026aacute;rdenas (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) discuss the impact of post-earthquake social housing reconstruction in Talca, Chile, where displaced residents were relocated to peripheral areas, disrupting established social fabrics and leading to socio-economic isolation.\u003c/p\u003e\u003cp\u003eSuch spatial fragmentation reinforces social exclusion and limits employment opportunities, a key mechanism in the perpetuation of poverty. Notably and as shown here, informal housing, despite its precarious conditions, sometimes offers better location advantages and social networks than formal social housing. This challenges the neoliberal emphasis on formalisation and suggests that location, infrastructure, and community integration are equally, if not more, important than legal tenure.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Spatial Outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey Finding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUrban Spatial Factor\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZunino \u0026amp; Hidalgo (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePeripheral, standardised complexes led to socio-economic polarisation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUrban segregation, Peripheralisation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDohnke (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInvestment prioritised affluent zones, marginalising low-income areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUrban segregation, Peripheralisation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFuster-Farf\u0026aacute;n (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMarket-driven planning failed to secure long-term urban integration for low-income residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUrban segregation, Peripheralisation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCelhay (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInformal settlements sometimes offered better social and locational benefits than formal housing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFunctional informality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInzulza \u0026amp; C\u0026aacute;rdenas (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEarthquake recovery policies relocated families away from original communities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDisplacement, Loss of social capital\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn summary, the above thematic review shows that structural conditions such as a neoliberal housing regime define policy outcomes. The evidence from Argentina and Chile indicates that the benefits of neoliberal housing policies are highly uneven and deeply conditioned by structural, economic, and spatial inequalities. Health, economic opportunities, social cohesion, and urban inclusion are not guaranteed by access to housing alone, especially when delivery models emphasise market logic over social equity. Policies that reinforce individual responsibility, deregulation, and formal ownership, hallmarks of the neoliberal model, frequently fail to disrupt the cycle of poverty and can even exacerbate it. In contrast, participatory, flexible, and community-rooted approaches, supported by strong regulatory frameworks and public investment, show greater promise in creating sustainable housing outcomes that empower low-income populations. Future housing strategies must therefore transcend market-driven paradigms and embrace holistic frameworks that prioritise human well-being, environmental quality, and spatial justice, breaking the links between inadequate housing and intergenerational poverty.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRisk of bias results: Reflections on Assessing Mixed-Methods Research in a Systematic Review\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAssessing the risk of bias in a systematic review that incorporates quantitative, qualitative, and mixed-methods studies presents a unique set of methodological and interpretive challenges. Recognising the epistemological diversity within the literature on neoliberal housing policies in Argentina and Chile, this review adopted a bespoke scoring system to ensure consistency, transparency, and fairness in the evaluation process. While this approach allowed for a nuanced comparison across disparate research designs, the results of the assessment also reveal key limitations in the existing literature and illustrate broader tensions in applying quality appraisal tools across methodological paradigms.\u003c/p\u003e\u003cp\u003eAdditional file 4 shows the final risk of bias assessment and scoring. None of the papers reviewed achieved the maximum weighted score of 1.25 points awarded to a hypothetical model paper that had an adequate sample size considering its methodological approach (1 point), appropriate study design (1 point), and data collection (1 point), as well as reporting all potential confounding factors (6 points). The highest scoring paper was Celhay (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) with 1.18 points, with a deduction for not reporting pre-existing health conditions in a study of 32 subsidised housing projects in Santiago, Chile. Although the aim of the paper was to compare household preferences between living in informal housing versus government-led subsidised housing, the exclusion of pre-existing health conditions poses a small risk to the results, as some households might prefer a location due to its proximity to health centres or other formal/informal care provisions. The next highest scoring paper is Burgos (2015) with 1.13 points. This paper reviews children\u0026rsquo;s health in government-led subsidised housing, finding positive effects compared to children in households living in slums. However, it only reports on two confounding factors: household income and housing conditions. The crucial factor of pre-existing health conditions is merely mentioned, as are other factors like education and crime rates. Other papers scoring above 1 (Flores Larsen 2021, 1 point; Lehner \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, 1.05; Gill, 20twenty-two, 1.05; and Torres et al \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, 1.10) all have similar issues of not reporting or not mentioning a confounding factor. The remaining papers that scored below 1 all failed to report a sample size (Cutts, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Flores-Larsen \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Vergara 2019; Orlando-Romero, 2023; Porras-Salazar, 2020; Perez, 2017; Dohnke, 2015; Ozler, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Perez, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; C\u0026aacute;ceres et al, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Stang et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zunino and Hidalgo, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Fuster-Farf\u0026aacute;n \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; and Fuentes and Rodriguez, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The lowest scoring paper is Inzunza and C\u0026aacute;rdenas (2017), which fails to report sample size and also has an inadequate study design. The shortcomings of the paper include the lack of diversity in the interviews (only 18 residents of the 238,817 reported in the paper that were affected by the earthquake). The team considered that the study needed a higher representative sample or a more diverse base of interviewees, such as including local authorities and NGOs operating after the earthquake, which could have provided a higher-level perspective of the entire neighbourhood. This example highlights how even methodologically valid qualitative work can falter when critical perspectives or sample representativeness are missing.\u003c/p\u003e\u003cp\u003eThe results underscores a broader issue: while many studies provide strong contextual or theoretical contributions, they often lack systematic reporting of confounding variables, limiting the generalisability of their findings. This reflects a broader trend in the literature: while there is an emphasis on policy-level analysis or structural critique, fewer studies engage in multi-variable, intersectional analysis that would clarify how various socio-economic conditions mediate the effects of housing policy. Given the complex realities of poverty, especially as it relates to housing, health, and employment, this omission weakens causal inferences and hampers policy translation.\u003c/p\u003e\u003cp\u003eOne of the most complex areas of risk assessment involved sample size. Recognising that qualitative research does not adhere to statistical generalisability in the same way as quantitative studies, the team assigned a lower weighting (15%) to this criterion. However, the fact remains that many studies failed to report sample size altogether, including several with rich empirical insights (for example Vergara 2019 and Orlando-Romero 2023). This lack of transparency, whether in interview-based, ethnographic, or survey research, limits the replicability and evaluative clarity of these works, and suggests the need for improved minimum reporting standards, regardless of study design.\u003c/p\u003e\u003cp\u003eIn sum, the application of a weighted, variable-based risk of bias assessment allowed this systematic review to maintain consistency across a methodologically diverse evidence base. However, the process also exposed significant limitations in the current literature, notably, inconsistent reporting of sample sizes and confounding variables, and varied attention to study design integrity. Ultimately, the difficulty of assessing mixed-methods studies lies not in their inclusion but in their standardised evaluation. While tools such as the one developed for this review represent a step forward, future systematic reviews should consider even more flexible frameworks that are attuned to the epistemological logics of each methodology, while still demanding transparency, accountability, and rigour. This exercise suggests that improving reporting practices, particularly for sample size, confounding variables, and data triangulation, would substantially raise the evaluative quality of policy-relevant research in this field. At the same time, risk of bias tools must continue to evolve to avoid penalising valid forms of qualitative inquiry that enrich our understanding of housing, poverty, and inequality in complex urban contexts. While our bespoke tool enabled consistent appraisal across diverse study types, its lack of formal external validation and the variability in reporting quality across studies represent important limitations that may affect the precision of comparative assessments.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis systematic review demonstrates that the outcomes of neoliberal housing policies for low-income families in Argentina and Chile are shaped by a complex interplay of structural, spatial, and institutional factors. The findings reveal that while housing provision under neoliberal regimes has succeeded in expanding homeownership and formalising tenure for many households, the benefits of these policies remain highly uneven and often insufficient to break the cycle of poverty.\u003c/p\u003e\u003cp\u003eAcross the thematic domains of health, economic security, social cohesion, and urban space, the review shows that market-driven housing strategies frequently externalise risk to residents, particularly in environments where regulatory oversight, social infrastructure, and public investment are weak or unevenly distributed. Poor-quality housing, inadequate insulation, and spatial segregation have direct and indirect consequences on residents\u0026rsquo; physical and mental health, limiting their capacity to engage in stable employment and undermining long-term economic resilience. Moreover, the promise of economic uplift through property ownership has largely failed to materialise for most beneficiaries of social housing. While formal tenure provides legal security, it rarely leads to enhanced access to credit or asset accumulation in contexts of economic precarity. In many cases, households remain locked into substandard or peripheral housing, disconnected from employment hubs and public services. Conversely, contextual and institutional variables, such as strong community organisation, participatory governance, and strategic location, can mitigate some of the adverse effects of neoliberal housing policies. Programs rooted in collaborative planning, community-led housing production, and the active involvement of third-sector organisations are associated with more positive outcomes across all thematic domains, particularly where they emphasise social cohesion, inclusion, and wellbeing alongside physical infrastructure.\u003c/p\u003e\u003cp\u003eFrom a methodological standpoint, the review also highlights the limitations of current research practices, including inconsistent reporting of key variables and a lack of intersectional analysis. The bespoke risk of bias assessment confirms that while many studies offer valuable insights, there is a need for greater methodological transparency and standardisation, particularly concerning sample size reporting and the treatment of confounding variables.\u003c/p\u003e\u003cp\u003eIn sum, the benefits of neoliberal housing policies are not determined solely by access to housing but by how housing is situated within a broader ecology of social policy, infrastructure, and equity. To ensure housing functions as a tool for poverty alleviation, policy frameworks must move beyond market logic and adopt integrated, equity-focused approaches that prioritise health, social cohesion, urban connectivity, and long-term economic sustainability.\u003c/p\u003e\u003cp\u003eFuture research should aim to fill geographical and methodological gaps, particularly in the underrepresented Argentinean and regional context, and should further investigate the roles of governance, institutional design, and community agency in shaping housing outcomes. Future systematic reviews in LMIC policy contexts should prioritise the development of adaptable, mixed-methods appraisal tools and context-sensitive synthesis frameworks that account for the complexity, data variability, and epistemological diversity characteristic of research in these settings. Only through such holistic and critical engagement can we advance towards housing systems that serve as engines of social inclusion rather than mechanisms of marginalisation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors are grateful for the funding and support provided by the Reading Real Estate Foundation; Fondecyt 11200793 ANID, Chile and Fondecyt ANID-SIA 85240235, Chile.\u003c/p\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003cp\u003eThe data supporting the findings of this study were obtained from publicly accessible bibliographic databases, including Scopus, Web of Science, and PubMed. All data used in the review are available through these repositories and can be accessed with appropriate institutional or individual subscriptions.\u003c/p\u003e\u003cp\u003eEthics, Consent to Participate, and Consent to Publish declarations: not applicable.\u003c/p\u003e\u003cp\u003eAuthors\u0026rsquo; contributions: The lead author conceptualised the study and led the development of the methodology and manuscript writing. All authors contributed to data collection and analysis, provided critical revisions, and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBaker, M., \u0026amp; Mason, J. (2012). The effects of neoliberal policies on housing and health: A critical review. \u003cem\u003eJournal of Housing and the Built Environment\u003c/em\u003e, 27(4), 453-468.\u003c/li\u003e\n\u003cli\u003eBaker, M., McDonald, A., Zhang, J., \u0026amp; Howden-Chapman, P. (2017). 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Spatial and Socioeconomic Effects of Social Housing Policies Implemented in Neoliberal Chile: The Case of Valpara\u0026iacute;so. \u003cem\u003eUrban Geography\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(5), 514-542. https://doi.org/10.2747/0272-3638.30.5.514\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"systematic-reviews","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sysr","sideBox":"Learn more about [Systematic Reviews](http://systematicreviewsjournal.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/sysr/default.aspx","title":"Systematic Reviews","twitterHandle":"@MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Housing and health, Latin America, framework synthesis, social determinants of health, neoliberal housing policies, Argentina, Chile","lastPublishedDoi":"10.21203/rs.3.rs-7196007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7196007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis systematic review responds to a critical gap in housing and health literature by examining how neoliberal housing policies impact low-income populations in Argentina and Chile. While existing reviews often link housing conditions to health outcomes, few consider the structural effects of neoliberal reforms that reframe housing as a commodity rather than a fundamental human need and a critical factor in health. Drawing on a framework synthesis of twenty-two studies from Argentina and Chile, we identify the institutional, spatial, and social mechanisms through which housing systems affect resident well-being. Using a structured matrix built on the PISO framework and informed by PRISMA guidelines, we analyse evidence across four interlinked domains: health, economic resilience, social cohesion, and urban spatial integration. Our findings reveal that neoliberal housing programs frequently externalise structural risks to residents, exacerbating vulnerability despite formal homeownership. The paper also introduces a bespoke risk of bias tool adapted for mixed-methods research, revealing pervasive gaps in methodological transparency of articles reviewed here. By integrating health into a broader structural critique, this review contributes to both the social housing and public health literature, demonstrating how market-led policies may entrench poverty rather than disrupt it. 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