SciELO - Scientific Electronic Library Online

 
vol.36 issue3Salutogenic strategies for the regeneration of degraded neighborhoodsThe preventive efforts of the Spanish autonomous regions and socio-economic inequality in childhood obesity or overweight author indexsubject indexarticles search
Home Pagealphabetic serial listing  

My SciELO

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Gaceta Sanitaria

Print version ISSN 0213-9111

Gac Sanit vol.36 n.3 Barcelona May./Jun. 2022  Epub Sep 30, 2022

https://dx.doi.org/10.1016/j.gaceta.2021.08.005 

Original Articles

Neglected housing insecurity and its relationship with renters health: the case of Barcelona, Spain

Inseguridad residencial desatendida y su relación con la salud de personas inquilinas: el caso de Barcelona, España

Constanza Vásquez-Veraa  b  c  *  , conception and design, manuscript revision, writing, manuscript approvement; Juli Carrereb  c  , conception and design, manuscript revision, manuscript approvement; Carme Borrella  b  c  d  , conception and design, manuscript approvement; Hugo Vásquez-Verab  c  , conception and design, manuscript revision, manuscript approvement

aUniversitat Pompeu Fabra, Departament de Ciències Experimentals i de la Salut, Barcelona, Spain

bAgència de Salut Pública de Barcelona, Barcelona, Spain

cInstitut de Recerca Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

dCIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain

Abstract

Objective:

To analyze by gender the relationship of forced displacements due to neglected housing insecurity with the physical and mental health of renters in Barcelona in 2019, distinguishing between economic (EHI) and legal (LHI) housing insecurity.

Method:

We conducted a cross-sectional study based on the Survey of the Living Conditions of Renters in the Barcelona Metropolitan Area 2019 (1021 women; 584 men). Self-reported health and mental well-being were the dependents variables; the main explanatory variable was neglected housing insecurity. We used adjusted robust Poisson regression models to compare health outcomes among people affected by neglected housing insecurity and those who were not affected.

Results:

We observed that the probability of worse health outcomes are greater in those affected by EHI, followed by those affected by LHI, both compared to those who have not been affected by housing insecurity. This association are mainly observed in mental health of renters affected by EHI, even after adjusting for socioeconomic and other housing variables (in women PR: 1,17, CI95%: 1,03-1,33; in men PR: 1,21, CI95%: 1,01-1,43).

Conclusions:

Neglected housing insecurity is associated with worse mental health. Enhancing the visibility of neglected housing insecurity and raising awareness of its effects on health is urgently needed to tackle this massive but hidden problem.

Keywords: Housing insecurity; Housing; Public health; Mental health; Physical health

Resumen

Objetivo:

Analizar la relación de la inseguridad residencial desatendida sobre la salud física y mental de personas inquilinas residentes en Barcelona en 2019, distinguiendo entre inseguridad residencial económica (IRE) y legal (IRL).

Método:

Estudio transversal basado en la Encuesta de Condiciones de Vida de Personas Inquilinas en el Área Metropolitana de Barcelona 2019 (1021 mujeres y 584 hombres). Las variables dependientes fueron salud autopercibida y bienestar mental, y la principal variable explicativa fue inseguridad residencial desatendida. Se utilizaron modelos ajustados de Poisson robusta para comparar los resultados de salud entre personas afectadas y no afectadas.

Resultados:

La probabilidad de peor salud fue mayor en las personas afectadas por IRE, seguidas por las afectadas por IRL, ambas comparadas con quienes no habían sido afectadas. Esta asociación fue principalmente observada en la salud mental de las personas inquilinas afectadas por IRE, incluso tras ajustar por variables sociodemográficas y otras de vivienda (en mujeres, PR: 1,17, IC95%: 1,03-1,33; en hombres, PR: 1,21, IC95%: 1,01-1,43).

Conclusiones:

La inseguridad residencial desatendida se asocia con peor salud mental. Se necesita urgentemente visibilizar la inseguridad residencial desatendida y tomar conciencia de sus efectos en la salud para así afrontar este masivo, pero oculto, problema.

Palabras clave: Inseguridad residencial; Vivienda; Salud pública; Salud mental; Salud física

Introduction

Currently, there is a widespread housing crisis, affecting millions of lives worldwide, and Europe is no exception.1 This problem has become more evident after the housing market bubble burst in 2007, forcing various European states to take measures to alleviate the consequences of the collapse of the mortgage market.2 These actions led to a shift in the housing bubble from property tenure to renting, as exemplified in Spain,3,4 Greece and Croatia.5,6 In the countries of the European Union, the rate of households allocating more than 40% of their income to rent has increased (rates from 26.2% to 28%, in 2012 and 2016, respectively), while this rate has decreased in households with mortgages (from 8.3% to 5.4%).5,6

Housing insecurity is a complex phenomenon that may affect people's lives related to the housing dimensions of accessibility/affordability and stability.7 These dimensions, in turn, are mainly linked to economic and legal issues,8,9 such as living without the security of legal tenure (sub-renting, squatting or doubling-up), or being under a legal eviction process.9

However, there are other cases of housing insecurity that are less visible, usually naturalized due to their ordinary nature and lack of formal records.10,11 This is the case of situations qualitatively different from the formal eviction process and which, therefore, do not involve a judicial or police process.10,11 These situations are neglected types of housing insecurity, which we have classified into economic housing insecurity (being forced to leave a dwelling due to abusive rent increases or loss of household income) and legal housing insecurity (being forced to leave a dwelling in the absence of a legal lease agreement or unilateral termination of a valid lease agreement).

In Spain, the movement of the housing market bubble toward rental tenure can be observed in several indicators. For example, in the 2013-2019 period, housing prices decreased, while rents increased by 50%. This trend occurred in all the provincial capitals of the country, such as Barcelona.12,13 This trend is inconsistent with the household income growth in the country, which increased by only 1.3% in the same period.14 Thus, in 2016, 43% of renters allocated 40% or more of their oncome to housing costs.6

Similarly, in this period, 440,107 evictions were registered in the country, 58% of them due non-payment of rent.15 The autonomous community with the most evictions during this period was Catalonia, with 100,935 evictions (23% of the national total), of which 64.8% were due to rental reasons.15 This situation is clearer in Barcelona city, where 84% of evictions are due to rent arrears.14 Even though homeowners are affected by housing-related problems, the housing crisis has increased among renters, reflecting the shift in the housing bubble from the property market to the rental market.6,14,15

Faced with this emergency housing context, various social movements emerged to tackle and safeguard people's right to housing.16 Thus, in 2017 the “Sindicat de Llogateres” (Renters’ Union) was formed in Barcelona, whose main objective is to foster the collective vindication of renters’ rights and to influence administrative and government-related policies.11

As far as we know, most of the studies on the topic have either addressed the problem of housing insecurity among owners or have not distinguished among types of tenure. Moreover, few studies have specifically addressed the relationship between housing insecurity and poor in renters.17-21 For example, regarding general health, a study of 27 countries of European Union concluded that persons with housing insecurity reported worse self-rated health than unaffected individuals. Moreover, the negative health effects on renters were greater than those experienced by people with other types of tenure, even after adjustment by other sociodemographic variables.18 The mental health effects of housing insecurity have been reported to be depression, anxiety and stress,17,19-21 mostly affecting women,20 single-parent households19 and those with lower incomes.17,18,21It has also been observed that these effects are maintained over years, related to insecurities in other areas of people's lives (food, work, family life, and others), and have greater negative effects on the mental health of renters than that of owners.17,19,20

Despite the severity of this housing emergency, so far there is insufficient evidence on the relationship between health and neglected housing insecurity in renters, hindering policy design to tackle this issue. This study aimed to analyze the association of housing insecurity, both in its legal and economic dimensions, with self-rated health and mental health by gender among renters in Barcelona city in 2019.

Method

We performed a cross-sectional study. The study population consisted of people over 18 years old who were renters living in Barcelona city and who voluntarily completed the self-administered web survey “Renters’ Living Conditions of the Barcelona Metropolitan Area 2019”. The survey was designed by the Sindicat de Llogateres, La Hidra Cooperativa and the Barcelona Public Health Agency and was disseminated by social networks. The secondary data were provided by the Sindicat de Llogateres and La Hidra Cooperativa. The survey collected sociodemographic, residential and health information from the rental upswing period between the years 2014-2019.22 Data were collected between March and May 2019 and, to ensure the independence of the observations, only one person was selected from each household. The survey was completed by 2051 individuals; subsequently, we excluded those not residing in Barcelona city. In addition, people who reported having been affected by formal evictions (n=8) were excluded as they were not part of the phenomenon to be studied. Thus, the study sample included 1637 participants (1021 women, 584 men, and 32 people not identifying with binary gender).

We used two measures of health status: mental health and self-rated health. Mental health was evaluated using the short version of the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS), which has been found to be a good proxy for mental health.23 The variable was categorized in two groups: mental well-being (>26 points) and mental discomfort (≤26 points).23,24 Self-rated health was evaluated using the 5-category question “How would you say your health is in general?” We created a dichotomous outcome variable: good health (excellent, very good, good) and poor health (fair, poor).25

The main explanatory variable, neglected housing insecurity, was constructed from two questions: “Have you changed your address in the last 5 years?” and “What was the main reason for this move?” We used this variable as categorical, including any of the following responses in the category “Legal Housing Insecurity” (LHI): “because the owner decided to end or not to renew the rental contract”, or “because the owner decided to evict me in the absence of a rental contract”. In contrast, the category “Economic Housing Insecurity” (EHI) was composed of persons who responded “due to financial difficulties because of the increase in housing prices” or “due to financial difficulties because of a decrease in household income”. Finally, the category “Without Housing Insecurity” was composed of both persons who did not move home and those who responded “it was a voluntary move, it was better adapted to my needs” or “it was a voluntary move, the dwelling was in poor physical condition”.

The following adjustment variables were included: employment status, occupational social class,26 age, nationality, rental situation, and risk of involuntary mobility in the next 6 months. Gender was treated as a stratification variable, based on the question “with which gender do you identify yourself?” (women, men, non-binary).

We carried out a descriptive analysis of the study variables to determine their distribution. Then, to carry out the next steps of the analysis, all persons not identifying with binary gender were excluded because there were very few cases (n=32), leaving a sample of 1605 individuals. Subsequently, a bivariate analysis was performed between the explanatory variable of the study and the sociodemographic and dependent variables, obtaining the prevalence between affected and unaffected people, and their magnitude of association using the chi-square or Fisher exact tests. Then, age-adjusted robust Poisson regression models (PRa) were fitted to compare health outcomes among people affected by neglected housing insecurity and those who were not affected. Finally, we calculated an adjusted model that included housing variables and the most relevant sociodemographic variables according to Wald's test (PRb). All the analyses were carried out stratifying by gender, using the statistical software STATA15.

Results

Analysis of the sociodemographic characteristics of the study sample showed that 50% of women were aged 35-50 years, while men and people with non-binary gender were mostly aged 18-34 years (45% and 46.9%) and 35-50 years (44.9% and 43.8%, respectively). Most participants were from Spain (∼90%). Regarding socioeconomic status, most reported being employed (women, 84.4%; men, 86.8%; non-binary gender, 84.8%) and belonging to managerial and senior professionals’ social classes (women, 63.9%; men, 58.6%; non-binary gender, 56.3%) (Table 1).

Table 1. Participants’ sociodemographic characteristics 

Independent sociodemographic variables Women (n=1021) Men (n=584) Non-binary gender (n=32) p
n % n % n %
Age (years)
18-34 397 38.9 263 45.0 15 46.9 0.22
35-50 512 50.2 262 44.9 14 43.8
51-60 67 6.6 37 6.3 1 3.1
61-87 37 3.6 14 2.4 1 3.1
Missing 8 0.8 8 1.4 1 3.1
Total 1021 100 584 100 32 100
Nationality
Spain 915 89.6 546 93.5 29 90.6 0.07
European Union 65 6.4 23 3.9 3 9.4
Non-European Union 40 3.9 15 2.6 -- --
Missing 1 0.1 -- -- -- --
Total 1021 100 584 100 32 100
Employment status
Employed 867 84.9 507 86.8 27 84.4 0.57
Unemployed 87 8.5 37 6.3 3 9.4
Other 65 6.4 39 6.7 2 6.3
Missing 2 0.2 1 0.2 -- --
Total 1021 100 584 100 32 100
Occupational social class
I-II 656 64.3 342 58.6 18 56.3 0.28
III-IV 206 20.2 124 21.2 8 25.0
V-VI-VII 103 10.1 75 12.8 4 12.5
Missing 56 5.5 43 7.4 2 6.3
Total 1021 100 584 100 32 100

For housing conditions, most renters reported that they individually paid all the rent and housing costs (40.6%, women; 41.6%, men; 37.5%, non-binary gender), followed by those who rented with more people sharing the housing costs (38.3%, women; 38%, men; 28.1%, non-binary gender). In addition, most participants reported they were not at risk of involuntary displacement in the next 6 months.

Analysis of neglected housing insecurity showed that, among women, 12.4% reported they were under LHI and 12.3% were under EHI. Among men, 14.9% reported they were under LHI and 9.3% under EHI. Among persons not identifying with binary gender, the percentages were 12.5% and 25%, respectively (Table 2).

Table 2. Participants’ housing and health characteristics 

Women (n=1021) Men (n=584) Non-binary gender (n=32)
n % n % n % p
Independent sociodemographic variables
Rental situation
Rent whole house 414 40.6 243 41.6 12 37.5 0.35
Shared economy 391 38.3 222 38.0 9 28.1
No shared economy 170 16.7 93 15.9 7 21.9
Rent room 42 4.1 25 4.3 4 12.5
Missing 4 0.4 1 0.1 -- --
Total 1021 100 584 100 32 100
Risk of involuntary mobility
No 547 53.6 340 58.2 19 59.4 0.22
Yes 134 13.1 79 13.5 2 6.3
Don’t know 339 33.2 165 28.3 11 34.4
Missing 1 0.10 -- -- -- --
Total 1021 100 584 100 32 100
Independent principal variable
Neglected housing insecurity
No 771 75.5 443 75.9 20 62.5 0.05
Yes, legal problems 128 12.5 87 14.9 4 12.5
Yes, economic problems 119 11.7 54 9.3 8 25.0
Missing 3 0.29 -- -- -- --
Total 1021 100 584 100 32 100
Dependents variables
Mental well-being
Mental well-being 381 37.3 222 38.0 7 21.9 0.17
Mental discomfort 636 62.3 357 61.1 25 78.1
Missing 4 0.4 5 0.9 -- --
Total 1021 100 584 100 32 100
Self-rated health
Good 901 88.3 525 89.9 27 84.4 0.44
Bad 120 11.8 56 10.1 5 15.6
Missing -- -- -- -- -- --
Total 1021 100 584 100 32 100

The group most affected by neglected housing insecurity, both legal and economic, were those renting a room (women, 19.1% and 31%, and men, 32% and 20%, respectively). The profile of people affected by LHI was mainly men from non-European Union countries (20%) and people who rented with other people without shared economy (women, 17.7%; men, 20.4%). EHI mainly affected people from the manual class (women, 13.6%; men, 12%) (Table 3).

Table 3. Percentages of explanatory variables and health outcomes in women and men affected by neglected housing insecurity 

Women (n=1021) Men (n=584)
No LHI EHI Total p No LHI EHI Total p
n % n % n % n % n % n % n % n %
Independent socio-demographic variables
Age (years)
18-34 291 73.7 52 13.2 52 13.2 395 100 0.167a 198 75.3 40 15.2 25 9.5 263 100 0.729b
35-50 391 76.5 64 12.5 56 11.0 511 100 197 75.2 39 14.9 26 9.9 262 100
51-60 48 71.6 10 14.9 9 13.4 67 100 33 89.2 3 8.1 1 2.7 37 100
61-87 35 94.6 1 2.7 1 2.7 37 100 11 78.6 2 14.3 1 7.1 14 100
Nationality
Spanish 694 76.1 114 12.5 104 11.4 912 100 0915a 416 76.2 80 14.7 50 9.2 546 100 0.8b
European Union 47 72.3 8 12.3 10 15.4 65 100 17 73.9 4 17.4 2 8.7 23 100
Non-European Union 30 75.0 5 12.5 5 12.5 40 100 10 66.7 3 20.0 2 13.3 15 100
Employment status
Employed 650 75.1 112 13.0 103 11.9 865 100 0.583a 391 77.1 71 14.0 45 8.9 507 100 0.232b
Unemployed 65 74.7 11 12.6 11 12.6 87 100 26 70.3 6 16.2 5 13.5 37 100
Other 54 84.4 5 7.8 5 7.8 64 100 25 64.1 10 25.6 4 10.3 39 100
Occupational social class
I-II 503 76.9 80 12.2 71 10.9 654 100 0.739a 255 74.6 52 15.2 35 10.2 342 100 0.646a
III-IV 150 72.8 30 14.6 26 12.6 206 100 97 78.2 19 15.3 8 6.5 124 100
V-VI-VII 77 74.8 12 11.7 14 13.6 103 100 57 76.0 9 12.0 9 12.0 75 100
Rental situation
Rent whole house 330 79.7 46 11.1 38 9.2 414 100 0.000a 190 78.2 32 13.2 21 8.6 243 100 0.014a
Shared economy 296 76.3 44 11.3 48 12.4 388 100 171 77.0 28 12.6 23 10.4 222 100
No shared economy 120 70.6 30 17.7 20 11.8 170 100 69 74.2 19 20.4 5 5.4 93 100
Rent room 21 50.0 8 19.1 13 31.0 42 100 12 48.0 8 32.0 5 20.0 25 100
Risk of involuntary mobility
No 411 75.6 78 14.3 55 10.1 544 100 0.171a 261 76.8 45 13.2 34 10.0 327 100 0.554a
Yes 101 75.4 12 9.0 21 15.7 134 100 56 70.9 15 19.0 8 10.1 76 100
Don’t know 259 76.4 38 11.2 42 12.4 339 100 126 76.4 27 16.4 12 7.3 159 100
Dependent variables
Mental well-being
Mental well-being 305 80.3 45 11.8 30 7.9 380 100 0.009a 175 78.8 33 15.1 14 6.2 222 100 0.142a
Mental discomfort 463 73.0 82 12.9 89 14.0 634 100 265 74.8 52 14.5 40 10.8 357 100
Self-rated health
Good 685 76.3 112 12.5 101 11.3 898 100 0.441a 402 76.6 77 14.7 46 8.8 525 100 0.395a
Bad 86 71.7 16 13.3 18 15.0 120 100 41 69.5 10 17.0 8 13.6 59 100

EHI: economic housing insecurity; LHI: legal housing insecurity.

p-value of the association between neglected housing insecurity and the study variables using chi-square test (a) or Fisher exact test (b).

The prevalence of mental discomfort showed a gradient, in which people affected by EHI reported a higher prevalence of mental discomfort (74.8%, women; 74%, men) than people affected by LHI (64.6%, women; 61.2%, men) and these, in turn, had a higher prevalence than those not reporting housing insecurity (60.3%, women; 60.2%, men), with this association being significant in women. Likewise, the PRa (95% confidence interval [95%CI]) of people affected by EHI was 1.2 (1.1-1.4) among women and 1.2 (1.0-1.5) among men compared with non-affected renters; the PRa (95%CI) of people affected by LHI was 1.1 (0.9-1.3) and 1.0 (0.8-1.2), respectively. The same gradient was observed for self-rated health: people affected by EHI reported a higher prevalence of poor self-rated health (15.1%, women; 14.1%, men) than people affected by LHI (12.5%, women; 11.5%, men), who, in turn, reported a higher prevalence than non-affected renters (11.1% women; 9.3%, men). In addition, the PRa (95%CI) of people affected by EHI was 1.6 (1.0-2.5) among women and 1.8 (0.9-3.7) among men compared to individuals without housing insecurity; in those who reported LHI, the PRa (95%CI) was 1.3 (0.8-2.1) and 1.4 (0.7-2.6), respectively.

When adjusting for sociodemographic variables, we found that women with EHI had a mental discomfort PRb of 1.2 (95%CI: 1.0-1.3) and that men with EHI had a PRb of 1.2 (95%CI: 1.0-1.4) compared to those without housing insecurity. The results for persons affected by LHI were not significant, although women affected by LHI showed a possible tendency to being so, with a mental discomfort PRb of 1.1 (95%CI: 1.0-1.3). Regarding self-rated health, women and men under EHI had a higher likelihood of poor health than those without housing insecurity, with a PRb of 1.5 (95%CI: 0.9-2.4) and 1.90 (95%CI: 0.9-3.9), respectively. The same result was observed in women and men under LHI, with a PRb of 1.3 (95%CI: 0.8-2.2) and 1.4 (95%CI: 0.7-2.8), respectively. However, none of these results were statistically significant (Table 4).

Table 4. Prevalence (%) of poor mental health and poor self-rated health, prevalence difference and prevalence ratio (age-adjusted and adjusted by other sociodemographic variables) in women and men affected by neglected housing insecurity 

Women (n=1021) Men (n=584)
% p PD RPa 95%CI RPb 95%CI % p PD RPa 95%CI RPb 95%CI
Mental discomfort
Neglected housing insecurity
No 60.3 0.0   1   1   60.2 0.1   1   1  
Legal problems 64.6   4.3 1.1 0.9-1.3 1.1 1.0-1.3 61.2   1.0 1.0 0.8-1.2 1.0 0.8-1.2
Economic problems 74.8   14.5 1.2 1.1-1.4 1.2 1.0-1.3 74.1   13.9 1.2 1.0-1.5 1.2 1.0-1.4
Poor self-rated health
Neglected housing Insecurity
No 11.2 0.4   1   1   9.3 0.4   1   1  
Legal problems 12.5   1.3 1.3 0.8-2.1 1.3 0.8-2.2 11.5   2.2 1.4 0.7-2.6 1.4 0.7-2.8
Economic problems 15.1   3.9 1.6 1.0-2.5 1.5 0.9-2.3 14.8   5.5 1.8 0.9-3.7 1.9 0.9-3.9

95%CI: 95% confidence interval; PD: prevalence difference; PRa: prevalence ratio age-adjusted; PRb: prevalence ratio adjusted by age, social class, employment status, rental situation and risk of involuntary mobility.

Discussion

This is the first study in Spain that shows the relationship between neglected housing insecurity and mental and physical health among renters. We found that the likelihood of worse health due to neglected housing insecurity was greater in renters affected by EHI, followed by people affected by LHI, both compared to those not affected by housing insecurity. This association were statistically significant in the mental health of renters affected by EHI, both women and men, even after adjustment for socioeconomic and other housing variables.

In this study, mental health was worse in both women and men affected by EHI than in people without housing insecurity. This finding is consistent with previous studies reporting that people who have been forced to leave their dwellings due to economic problems have more mental health problems such an anxiety, depression, stress and lack of control.17,19,20,27 For instance, a previous study with people under different stages of housing insecurity showed that persons who had been forced to leave their dwellings due to financial problems in the last three years were more likely to report recent anxiety attacks.27 Furthermore, two studies conducted in low-income renters with housing insecurity found that they had worse mental health than those without housing insecurity and, also, reported that renters with housing insecurity problems were more likely to delay seeking healthcare due to financial reasons.17,28 In addition, the authors reported that renters with housing insecurity were more likely to experience insecure conditions in other areas such as work, family, food, study, and interpersonal relationships.8,17,28-30 According to Hulse and Saugeres,17 these situations of housing insecurity could contribute to the coexistence of diverse insecurities in people's lives that would be aggravated and produce negative effects on people's health and the generational transmission of this precariousness.

Mental health was slightly worse in women affected by LHI, although this difference was not significant. However, studies from the United Kingdom have reported that being forced to leave housing due to unilateral termination of a valid lease agreement or not being able to renew the lease generates negative psychosocial effects such as lack of control and a loss of the sense of belonging, as people have to move and restart daily routines elsewhere;31,32 these problems of neglected housing insecurity can also lead to an excess responsibility among affected persons, because there is often a lack of legal guarantees in housing policies for people experiencing these underground phenomena.10,33 It has been reported that these elements operate as mechanisms that affect people's mental health.7,17

In this study, self-rated health was worse in persons affected by EHI and LHI than among unaffected individuals. Although these results were not statistically significant, the prevalence ratios were large enough to suggest that greater statistical power would have confirmed this trend. Moreover, other studies of formal evictions have reported an evident negative effect on people's health.28,34 Formal eviction is more traumatic situation which affects health faster than neglected eviction; however, when this latter become repetitive, may reaches the same extent of negative health consequences than formal eviction.27 This association need to be further investigated.

The sample was mainly composed of people aged between 18 and 50 years and with Spanish nationality, which is consistent with observed data of the renter population in the Barcelona Health Survey.35 The distribution of managers and senior professionals in the sample was approximately double that of the Barcelona renter population (∼31%).35 Consequently, if the sample had been more representative of the population of Barcelona, a stronger association would probably have been observed between housing insecurity and health outcomes, because it is well-known that people from disadvantaged groups, such as the manual social class, have worse health status than people from more advantaged groups.19,21 People not identifying with binary gender had more EHI problems and worse health outcomes than women and men. This finding is consistent with studies indicating that transgender and non-conforming gender people experience more discrimination than cisgender people in terms of housing and employment.36 Moreover, worse health outcomes are associated with several forms of discrimination that constrain opportunities and access to basic aspects of life.37 Further in-depth studies are needed to investigate the association in these and other disadvantaged groups (e.g. children and elderly).

One of the limitations of this study is that the sampling method did not allow us to obtain a representative sample of renters in Barcelona and could have introduced selection bias, because it did not include renters affected by neglected housing insecurity but who were unable to participate (e.g., individuals without access to online services, the elderly). Such individuals would likely have even poorer health, and therefore the associations would have been stronger. Second, some categories had a very low sample, and consequently the findings should be interpreted with caution. Third, the magnitude of the association between health outcomes and housing insecurity may have been lost, due to the time interval between exposure and the observation of results; however, self-rated health is a stable indicator of people's health status.25

Despite these limitations, a strength of the study is that we constructed variables that allow an approach to the measurement and visibility of the phenomenon of neglected housing insecurity. This approach could contribute to future studies of invisible evictions, which are currently seriously affecting the Spanish context. In addition, this study is replicable in other contexts since we employed questionnaires that are used in European population studies. Moreover, the collaboration with the Sindicat de Llogateres allowed us to forge alliances between the academic and civil sectors to contribute to change country's housing policies. Finally, and closely related to the use of the online survey platform, another strength of the study is the cost-benefit and time-benefit ratio with which we were able to carry out recruitment.

Neglected housing insecurity is a phenomenon that currently affects many renters. These situations are associated with worse mental health. There is a need for neglected housing insecurity indicators to measure these phenomena and facilitate preventive interventions for this massive but hidden problem. In this regard, the study provides evidence that increases the visibility of this social reality and raises awareness of its implications, thereby contributing to the debate on solutions to this new housing emergency. Further studies are needed to continue investigate the relationship between neglected housing insecurity and renters health.

What is known about the topic?

Housing is recognized as a social determinant of health, affect people's health. To date, only a few studies have addressed the relationship between different types of housing insecurity and poor general and mental health in renters.

What does this study add to the literature?

Neglected housing insecurity was associated with worse mental health. In those affected for economic reasons it was significantly associated even after adjusting for socioeconomic and other housing variables

What are the implications of the results?

The study provides evidence that increases the visibility of neglected housing insecurity and raises awareness of its effects, thereby contributing to the debate on solutions to this new housing emergency.

Editor in charge

Carlos Álvarez Dardet.

Transparency declaration

The corresponding author on behalf of the other authors guarantee the accuracy, transparency and honesty of the data and information contained in the study, that no relevant information has been omitted and that all discrepancies between authors have been adequately resolved and described.

Ethics approval and consent to participate

The study was conducted according to the guidelines ofthe Declaration of Helsinki, and approved by the Ethics Committee of Parc de Salut Mar, Barcelona, as part of the project named “Desahucios invisibles” (n.◦ 2020/9104). Informed consent was obtained from all subjects involved in the study.

Acknowledgments

The authors thank the Sindicat de Llogateres (Renters Union) for its participation and for access to the study data, the Hidra Cooperative for its contribution to data collection, and the people who participated in the survey.

References

1. Pittini A, Laino E. Housing Europe Review. The Nuts and Bolts of European Social Housing Systems. 2012. Available at: https://www.housingeurope.eu/resource-105/the-housing-europe-review-2012. [ Links ]

2. Enoch C, Everaert L, Tressel T, et al. From fragmentation to financial integration in Europe. 2013. Available at: https://www.elibrary.imf.org/view/books/071/20740-9781484387665-en/20740-9781484387665-en-book.xml. [ Links ]

3. Bolsas y Mercados Españoles (BME), Jones Lang LaSalle (JLL). SOCIMIs. Estabilidad e inversión en el sector inmobiliario. Informe de Mercado. 2019. Available at: https://www.bolsasymercados.es/docs/BME/docsSubidos/SOCIMIsBMEJLL2019.pdf. [ Links ]

4. García-López MA, Jofre-Monseny J, Martínez Mazza R, et al. Do short-term rental plataforms affect housing markets? Evidence from Airbnb in Barcelona. J Urban Econ. 2020;119:103278. Available at: https://www.sciencedirect.com/science/article/pii/S0094119020300498. [ Links ]

5. Eurostat. Living Conditions in Europe - 2014 Edition. 2014. Available at: https://ec.europa.eu/eurostat/web/products-statistical-books/-/KS-DZ-14-001. [ Links ]

6. Eurostat. Living Conditions in Europe - 2018 Edition. 2018. Available at: https://ec.europa.eu/eurostat/web/products-statistical-books/-/KS-DZ-18-001. [ Links ]

7. Cortés Alcalá L. Indagaciones sobre la exclusión residencial. Arx Sociol. 2004;10:39-55. [ Links ]

8. Vásquez-Vera H, Fernández A, Novoa AM, et al. Our lives in boxes: perceived community mediators between housing insecurity and health using a PHOTOVOICE approach. Int J Equity Health. 2019;18:1-14. [ Links ]

9. Brändle G, García-Luque O. Measuring housing exclusion using the ETHOS typology. Housing, Care Support. 2015;18:113-24. [ Links ]

10. Palomera J. Els sindicats de llogaters i la lluita per l'habitatge en el nou cicle de financiarització. Pap Regió Metrop Barcelona Territ Estratègies, Planejament. 2018;0:156-63. [ Links ]

11. Rodríguez-Dod EC. But My Lease Isn't Up Yet!": Finding Fault with "No- Fault" Evictions. UALRL Rev. 2012;35:839. [ Links ]

12. Banco de España. Evolución reciente del mercado del alquiler de vivienda en España. Boletín Económico. 2019;3. Available at: https://www.bde.es/bde/es/secciones/informes/analisis-economico-einvestigacion/boletin-economico/index2019.html. [ Links ]

13. Observatori Metropolità de l'Habitatge de Barcelona. L'habitatge a la metrópoli de Barcelona 2018. Published online 2019:55. Available at: https://www.ohb.cat/wp-content/uploads/2019/07/Habitatgemetropolis2018.pdf. [ Links ]

14. Trilla C, Bosch J, Donat C, et al. Vivienda y derechos sociales en el área metropolitana de Barcelona. Barcelona: AMB; 2019. Available at: https://www.researchgate.net/publication/336058211_Vivienda_y_derechos_sociales_en_el_area_metropolitana_de_Barcelona. [ Links ]

15. Consejo General del Poder Judicial. Datos sobre el efecto de la crisis en los órganos judiciales TSJ hasta 2019. Published online 2020. Available at: https://bityli.com/KUvvvG. [ Links ]

16. Anzano Bergua X. Sindicat de Llogaters i Llogateres. El inquilinato insumiso. 2018 (Accessed September 22, 2019.) Available at: http://hdl.handle.net/10609/91293. [ Links ]

17. Hulse K, Saugeres L. Housing insecurity and precarious living: an Australian exploration. AHURI Final Rep. 2008:1-51. [ Links ]

18. Clair A, Reeves A, Loopstra R, et al. The impact of the housing crisis on selfreported health in Europe: multilevel longitudinal modelling of 27 EU countries. Eur J Public Health. 2016;26:788-93. [ Links ]

19. Desmond M. Unaffordable America: poverty, housing, and eviction. Fast Focus Inst Res Poverty. 2015;22:1-6. [ Links ]

20. Desmond M, Kimbro RT. Eviction's fallout: housing, hardship, and health. Soc Forces. 2015;94:295-324. [ Links ]

21. Novoa AM, Ward J, Malmusi D, et al. How substandard dwellings and housing affordability problems are associated with poor health in a vulnerable population during the economic recession of the late 2000s. Int J Equity Health. 2015;14:1-11. [ Links ]

22. Banco de España. El mercado de la vivienda en España entre 2014 y 2019. Documentos Ocasionales. 2020. Available at: https://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosOcasionales/20/Fich/do2013.pdf. [ Links ]

23. Castellví P, Forero CG, Codony M, et al. The Spanish version of the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) is valid for use in the general population. Qual Life Res. 2014;23:857-68. [ Links ]

24. Alayo I, Forero G, Vilagut G, et al. Reducción y validación de la escala WEMWBS (Warwick-Edimburgh Mental Well-Being Scale). 2019. In: XXX VII Reunión Científica de La Sociedad Española de Epidemiología y XIV Congresso Da Associação Portuguesa de Epidemiologia, Oviedo, Spain. 2019. Available at: https://www.gacetasanitaria.org/es-vol-33-num-sc-sumario-X0213911119X00C10. [ Links ]

25. Quesnel-Vallée A. Self-rated health: caught in the crossfire of the quest for "true" health? Int J Epidemiol. 2007;36:1161-4. [ Links ]

26. Domingo-Salvany A, Bacigalupe A, Carrasco JM, et al. Propuestas de clase social neoweberiana y neomarxista a partir de la Clasificación Nacional de Ocupaciones 2011. Gac Sanit. 2013;27:263-72. [ Links ]

27. Burgard SA, Seefeldt KS, Zelner S. Housing instability and health: findings from the Michigan recession and recovery study. Soc Sci Med. 2012;75:2215-24. [ Links ]

28. Meltzer R, Schwartz A. Housing affordability and health: evidence from New York City. Hous Policy Debate. 2016;26:80-104. [ Links ]

29. Burke T, Pinnegar S, Phibbs P, et al. Experiencing the housing affordability problem: blocked aspirations, trade-offs and financial hardships [Internet]. Melbourne, Australia; 2007. Available from: https://apo.org.au/node/3542. [ Links ]

30. Kirkpatrick SI, Tarasuk V. Housing circumstances are associated with household food access among low-income urban families. J Urban Health. 2011;88:284-96. [ Links ]

31. McKee K, Soaita AM. The "frustrated" housing aspirations of generation rent. UK Collab Cent Hous Evid. 2018; (August.). [ Links ]

32. Bone J. Neoliberal nomads: housing insecurity and the revival of private renting in the UK. Sociol Res Online. 2014;19:2-3. [ Links ]

33. Christudason A, Kenna P. Can housing rights be applied to modern housing systems? Int J Law Built Environ. 2010;2:103-17. [ Links ]

34. Vásquez-Vera H, Rodríguez-Sanz M, Palència L, et al. Foreclosure and health in Southern Europe: results from the Platform for People Affected by Mortgages. J Urban Health. 2016;93:312-30. [ Links ]

35. Bartoll X, Pérez K, Pasarín M, et al. Resultats de l'Enquesta de Salut de Barcelona 2016/17. Available at: https://www.aspb.cat/wpcontent/uploads/2018/07/Enquesta-salut-Barcelona-2016-17.pdf. [ Links ]

36. Kattari SK, Whitfield DL, Eugene Walls N, et al. Policing gender through housing and employment discrimination: comparison of discrimination experiences of transgender and cisgender LGBQ individuals. J Soc Social Work Res. 2015;7:427-47. [ Links ]

37. White Hughto JM, Reisner SL, Pachankis JE. Transgender stigma and health: a critical review of stigma determinants, mechanisms, and interventions. Soc Sci Med. 2015;147:222-31. [ Links ]

FundingNone.

Received: June 21, 2021; Accepted: August 21, 2021; pub: November 03, 2021

* Corresponding author. E-mail address: extcvasquez@aspb.cat (C. Vásquez-Vera).

Conflicts of interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Authorship contributions

Conception and design of the work: C. Vásquez-Vera, J. Carrere, H. Vásquez-Vera and C. Borrell. Analysis and interpretation of the data: C. Vásquez-Vera, J. Carrere and H. Vásquez-Vera. Writing of the article: C. Vásquez-Vera. Approval of the final version for publication: J. Carrere, C. Borrell and H. Vásquez-Vera. To be responsible for ensuring that all aspects of the manuscript have been reviewed and discussed among the authors: C. Vásquez-Vera

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License