International Journal of Environmental Research and Public Health Article Social Inequalities in Mental Health and Self-Perceived Health in the First Wave of COVID-19 Lockdown in Latin America and Spain: Results of an Online Observational Study Carmen Salas Quijada 1,† , Natalia López-Contreras 2,† , Tomás López-Jiménez 3,4,5 , Laura Medina-Perucha 3,4,5 , Brenda Biaani León-Gómez 6 , Andrés Peralta 7 , Karen M. Arteaga-Contreras 8 , Anna Berenguera 3,4,5,9 , Alessandra Queiroga Gonçalves 5,10,11 , Olivia Janett Horna-Campos 12 , Marinella Mazzei 12 , Maria Sol Anigstein 12,13 , Jakeline Ribeiro Barbosa 14 , Olga Bardales-Mendoza 15 , Joan Benach 16,17,18 , Daiane Borges Machado 19,20 , Ana Lucía Torres Castillo 7 and Constanza Jacques-Aviñó 3,4,5, * 1 Facultad de Medicina, Universidad Austral de Chile, Valdivia 5110566, Chile 2 Vicerrectoría de Investigación y Postgrado, Universidad de La Frontera, Temuco 4811230, Chile 3 Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 08007 Barcelona, Spain 4 Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain 5 Network for Research on Chronicity, Primary Care, and Health Promotion (RICAPPS), Spain 6 Unitat de Suport a la Recerca Metropolitana Nord, Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 08303 Mataró, Spain 7 Public Health Institute, Pontificia Universidad Católica del Ecuador (PUCE), Quito 170525, Ecuador 8 Servicios de Atención Psiquiátrica, Anillo Periférico #2767, Ed.5 P.B., Alcaldía La Magdalena Contreras, Cuidad de México 10200, Mexico 9 Departament d’Infermeria, Universitat de Girona, Emili Grahit, 77, 17003 Girona, Spain Citation: Salas Quijada, C.; 10 Unitat de Suport a la Recerca Terres de l’Ebre, Fundació Institut Universitari per a la Recerca a l’Atenció López-Contreras, N.; López-Jiménez, Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain T.; Medina-Perucha, L.; León-Gómez, 11 Unitat Docent de Medicina de Família i Comunitària Tortosa-Terres de L’Ebre, Institut Català de la Salut, B.B.; Peralta, A.; Arteaga-Contreras, 43500 Tortosa, Spain K.M.; Berenguera, A.; Queiroga 12 Escuela de Salud Pública “Salvador Allende”, Facultad de Medicina, Universidad de Chile, Gonçalves, A.; Horna-Campos, O.J.; Santiago 8380000, Chile 13 Departamento de Antropología, Universidad de Chile, Santiago 6850331, Chile et al. Social Inequalities in Mental 14 Center for Epidemiology and Health Surveillance, Oswaldo Cruz Foundation, Brasília 70904-130, Brazil Health and Self-Perceived Health in 15 Facultad de Educación, Universidad Peruana Cayetano Heredia, Lima 15102, Peru the First Wave of COVID-19 16 Research Group on Health Inequalities, Environment, and Employment Conditions (GREDS-EMCONET), Lockdown in Latin America and Universitat Pompeu Fabra, 08002 Barcelona, Spain Spain: Results of an Online 17 Johns Hopkins University-Universitat Pompeu Fabra Public Policy Center (UPF-BSM), 08002 Barcelona, Spain Observational Study. Int. J. Environ. 18 Ecological Humanities Research Group (GHECO), Universidad Autónoma de Madrid, 28049 Madrid, Spain Res. Public Health 2023, 20, 5722. 19 Center of Data and Knowledge Integration for Health, Gonçalo Moniz Institute, Oswaldo Cruz Foundation, https://doi.org/10.3390/ Salvador 41745-715, Brazil ijerph20095722 20 Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA 02115, USA * Correspondence: cjacques@idiapjgol.info or cjacques18@yahoo.es; Tel.: +34-93-482-46-1 Academic Editor: Kevin Pottie † These authors contributed equally to this work. Received: 30 January 2023 Revised: 29 March 2023 Abstract: COVID-19 lockdowns greatly affected the mental health of populations and collectives. Accepted: 19 April 2023 This study compares the mental health and self-perceived health in five countries of Latin America Published: 4 May 2023 and Spain, during the first wave of COVID 19 lockdown, according to social axes of inequality. This was a cross-sectional study using an online, self-managed survey in Brazil, Chile, Ecuador, Mexico, Peru, and Spain. Self-perceived health (SPH), anxiety (measured through GAD-7) and depression (measured through PHQ-9) were measured along with lockdown, COVID-19, and social Copyright: © 2023 by the authors. variables. The prevalence of poor SPH, anxiety, and depression was calculated. The analyses were Licensee MDPI, Basel, Switzerland. stratified by gender (men = M; women = W) and country. The data from 39,006 people were analyzed This article is an open access article distributed under the terms and (W = 71.9%). There was a higher prevalence of poor SPH and bad mental health in women in all conditions of the Creative Commons countries studied. Peru had the worst SPH results, while Chile and Ecuador had the worst mental Attribution (CC BY) license (https:// health indicators. Spain had the lowest prevalence of poor SPH and mental health. The prevalence creativecommons.org/licenses/by/ of anxiety and depression decreased as age increased. Unemployment, poor working conditions, 4.0/). inadequate housing, and the highest unpaid workload were associated with worse mental health Int. J. Environ. Res. Public Health 2023, 20, 5722. https://doi.org/10.3390/ijerph20095722 https://www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2023, 20, 5722 2 of 23 and poor SPH, especially in women. In future policies, worldwide public measures should consider the great social inequalities in health present between and within countries in order to tackle health emergencies while reducing the health breach between populations. Keywords: COVID-19; social impact; lockdown; mental health; inequities; self-perceived health 1. Introduction In order to contain the transmission of COVID-19, countries implemented measures such as movement restrictions with a strong impact on transportation, food security, the economy, and access to healthcare and education [1]. These drastic changes had psycholog- ical repercussions, bringing with them emotional conflicts, depression, stress, insomnia, and changes in health behaviors [2,3]. These symptoms varied according to the social and material conditions of people’s lives and according to social axes of inequality such as gender, age, territory, or socioeconomic position [4–6]. Likewise, women have been the most relevant workforce in health services that have contained the pandemic, a labor sector with the worst results in mental health [7]. In Latin America (LA), women are more present in the informal sector, have less capacity to deal with socioeconomic problems, and are the main caregivers at home [8]. In LA countries, a worse quality of life [9] and greater emotional distress have been observed among young people [10], especially women [11], as an effect of COVID-19 lockdown. In addition, self-perceived health (SPH)—an indicator of people’s health, the use of health services, and mortality [12,13]—has worsened, especially among older women [14]. LA is one of the most unequal regions in the world, with large cultural, social, and eco- nomic differences between and within countries [15]. In 2020, the Gini index of inequality was 48.9 in Brazil, 45.4 in Mexico, 47.3 in Ecuador, 44.9 in Chile, and 43.8 in Peru, showing high inequality compared to 34.3 in Spain [16]. Currently, LA has been one of the regions most affected by the COVID-19 pandemic in the world, with significant contractions in the middle-income population and an increase in inequality and poverty that has affected women, young people, migrants, and less educated workers the most [17]. The high level of informal work and the inability of governments to provide socioeconomic support for basic subsistence made compliance with the restrictions even more difficult [18]. For its part, in Spain, Temporary Employment Regulation Records (ERTEs) were applied (70% of salary), especially in activities classified as “nonessential”, which affected women’s em- ployment more and deepened the wage gap [19]. In LA, most countries closed educational establishments for at least three semesters, while Spain closed for 4 months [20]. Moreover, Peru was among the strictest in home containment, and Brazil was among the most lax [15]. On the other hand, the pandemic arrived in the midst of strong social conflicts, with Chile, Peru, and Ecuador were immersed in a major sociopolitical crisis, questioning government institutions [15]. This diversity of contexts suggests the existence of a differentiated impact on mental health and SPH between LA countries and Spain. The latter has a more developed welfare state, but relatively similar sociocultural characteristics to LA. For this reason, Spain and five LA countries were studied: Brazil, Chile, Ecuador, Mexico, and Peru. This information is particularly relevant for the development of strategies for targeting resources to the most vulnerable populations, as well as creating policies and developing public strategies. 1.1. Brief Socio-Sanitary Context A brief contextualization of the countries analyzed is given below. 1.1.1. Brazil The health emergency caused by the COVID-19 pandemic was marked by an adverse political context. In general, the federal executive (Bolsonaro was president at the time) Int. J. Environ. Res. Public Health 2023, 20, 5722 3 of 23 was against the adoption of the main measures recommended by experts, such as the use of masks and social isolation. Brazil never adopted a total shutdown of the country; social isolation was carried out irregularly. In this scenario, Brazilian society experienced an intensification of the political polarization already present since the last presidential elections [15,21,22]. 1.1.2. Chile The pandemic came at a time of strong discontent and social protest in response to a neoliberal model inherited from the Pinochet dictatorship. Public policies implemented by the Chilean government focused on social distancing and population control. A State of catastrophe was implemented, which included a curfew. Subsequently, the use of masks was made mandatory; sanitary customs were created; partial and total quarantines were established, differentiated by cities, with fines and sanctions for those who violated the lockdown. According to the Chilean neoliberal model, the state plays a subsidiary role, reflected in public economic policies, which initially focused on “employment protection”, giving the possibility of suspending workers’ salaries and tax payments for 3 months in favor of companies [15,21,23]. 1.1.3. Ecuador In this country, given the situation of a public health system in decline, in the first months, a first lockdown and curfew were decreed as a contagion control measure, allowing the sectors of primary need to maintain mobility to fulfill their functions; in addition, the country closed its borders, educational institutions and shopping centers were closed, and the use of masks in public spaces was established. Subsequently, the country’s sanitary traffic light was planned, with different measures according to the number of infections. At the end of May 2020, “social distancing” was proposed, a period in which the different municipalities would develop pilot plans for the progressive return to operation of the productive sectors, including educational centers and recreational services such as shopping centers [15,21,24]. 1.1.4. Mexico At the beginning of the pandemic, the national promotion of basic hygiene measures was initiated with emphasis on the most vulnerable populations in terms of health status. In view of the increase in infections and community transmission of the virus, preventive measures were intensified. Classes, events, and meetings were suspended, as well as all actions involving crowds of people. Although lockdown was indispensable, it was never made mandatory, since more than 50% of the population was in the informal economy; hence, they lacked social security, and it was impossible for this population to protect themselves. In the case of the formal economy, people worked exclusively in sectors considered basic necessities, such as services and basic products [15,21,25]. 1.1.5. Peru The government, before other countries in the region, declared a national health emergency and issued various measures for the prevention and control of the disease. At the same time, it ordered social isolation or so-called compulsory lockdown throughout the country. A national quarantine extended to all Peruvian citizens was indicated from 16 March to 31 December 2020, but with restrictive measures in a differentiated manner for each department or province, according to the prevalence of positive cases from 1 July to 31 December 2020. In 2021, some economic activities were reestablished to avoid further poverty and control the economic impact for the country, with some restrictions in the province and limitations on the exercise of freedom of movement of people [15,21,26]. 1.1.6. Spain A total lockdown of the population was declared by means of a state of alarm. The declaration of the state of alarm implied the closure of establishments and workplaces, Int. J. Environ. Res. Public Health 2023, 20, 5722 4 of 23 as well as the prohibition of certain activities. Freedom of movement was restricted with the exception of the purchase of basic necessities, the attendance of health services, and the assistance and care of dependents. By the end of April 2020, COVID-19 cases were declining, and a four-phase de-escalation or closure plan called the “plan for transition to a new normal” was approved. The plan included a series of measures, while easing restrictions on mobility and social contact, and allowing certain businesses and services to open to the public. After the de-escalation, decisions on control measures began to fall to the Spanish autonomous communities [21,27]. 1.2. Mental Health and Self-Perceived Health Problems A review quantified the prevalence and burden of depressive and anxiety disorders by age, sex, and location worldwide. Women and younger age groups were more affected than men and older age groups. They estimated large increases in prevalence in Latin America and the Caribbean, despite not finding any surveys from these regions that met their inclusion criteria [3]. In studies of countries in the region, in addition to the factors mentioned (i.e., con- sidering women and younger people), worsening mental health is associated with being attentive to news about the pandemic, having someone close diagnosed with COVID-19, the possibility of getting sick, loss of contact with peers [28], feeling a greater burden in taking care of children, taking medication on a regular basis, having a lower family income [29], not having a partner [6], and having poor sleep quality [30]. In the case of self-perceived health, there are studies that showed a relationship with having informal work, being a student or retired, reporting gender violence [14], having solely public healthcare system access, having COVID-19, and presence of any chronic illness [24], factors that increased the probability of having poor self-reported health status. However, there is limited evidence in comparative studies about mental health and self-perceived health in the region. 1.3. Research Question and Objective On the basis of this diverse context in terms of the measures implemented, we posed the following questions: (a) How has mental health and self-perceived health been ac- cording to the measures implemented for the management of the pandemic by COVID-19 in Latin American countries and Spain? (b) How did these outcomes differ according to inequality axes? Therefore, the aim of this study was to compare mental health status and self-perceived health in several LA countries and Spain during the lockdown of the first wave of the COVID-19 pandemic, according to several social factors. 2. Materials and Methods 2.1. Study Design and Data Source A cross-sectional descriptive study was conducted using a self-administered online survey of people aged 18 and over living in Brazil, Chile, Ecuador, Mexico, Peru, and Spain. Data collection was carried out in 2020 during the first wave between June and August (Brazil), May and August (Chile and Mexico), July and October (Ecuador), July and September (Peru), and April and May (Spain). The questionnaire was designed by a multidisciplinary research team in Spain and adapted to the specific context of each country. A pilot study was conducted prior to dissem- ination in order to represent the sociodemographic diversity of each country’s population. At the beginning of the survey, the objective of the study and the duration of the survey were explained, which lasted approximately 10 min, including the reading and signing of the informed consent. In Spain, the REDCap (Research Electronic Data Capture) platform was used, an electronic data capture tool hosted at the Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol). REDCap is a secure, web-based software platform designed to support data capture for research studies, providing (1) an intuitive interface for validated data capture, (2) audit trails for tracking data manipulation and export procedures, (3) automated export procedures for seamless Int. J. Environ. Res. Public Health 2023, 20, 5722 5 of 23 data downloads to common statistical packages, and (4) procedures for data integration and interoperability with external sources [31,32]. For LA, survey data were collected and managed using SurveyMonkey® electronic data capture tools (hosted by IDIAPJGol). Our study was approved by the Research Ethics Committee of the Institut de Recerca en Atenció Primària Jordi Gol i Gurina (IDIAPJGol) (ref. REC 20/063-PCV). 2.2. Sampling Data collection was carried out through the online platforms of each of the participat- ing centers in the different countries and their respective social networks and mass media, using convenience and snowball sampling techniques. 2.3. Variables The main study variables were mental health problems (anxiety and depression) and SPH. Anxiety was defined as persistent worry and anticipatory responses to future threats, as measured by the Generalized Anxiety Disorder (GAD-7) screening tool; it was classified according to the score obtained as “normal/no anxiety” and “moderate to severe” [33,34]. Depression was defined as marked feelings of sadness, emptiness, or irritability, assessed by the Patient Health Questionnaire (PHQ-9) and classified as “minimal/mild” or “moderate/severe” [33,34]. The SPH (“How would you say your overall health is?”) has five Likert-scale response options, which were recategorized into “good” and “poor”. For the mental health outcomes, depression and anxiety scales were used, which have been validated in all countries participating in the study [35–40]. The sociodemographic variables and those related to pandemic lockdown were gender identity, educational level, age, indigenous group membership, country of birth, pre- pandemic employment status, change in employment status, housing tenure, perception of adequate housing, household composition, presence of children and/or dependents in the household, household work, concern about living with household members, and concern about school education (see Table A1 for details of variables). 2.4. Statistical Analysis A descriptive analysis of all variables of interest was performed to obtain absolute numbers and percentages. The chi-square test was used to determine if there were differ- ences between sexes. The prevalence of self-perceived poor health, anxiety, and depression was calculated. Analyses were stratified by sex (men/women) and country. All statistical analyses were performed using Stata version 15.1 software. 3. Results Data from 39,006 people who completed the survey were analyzed (see Table A2 for distribution of missing values). Of the total number of respondents, the majority were female (71.9%), between 35 and 64 years old (58.8%), with a university education (73.0%), a trend that was repeated in all countries in the following order of representation: Brazil (35.8%), Mexico (21.5%), Spain (18.7%), Chile (14.4%), Ecuador (6.8%), and Peru (2.9%) (Table 1) (see Table A3 for complete data). 3.1. Self-Perceived Health (SPH) There was a higher prevalence of poor SPH in women than in men in all countries studied. The highest prevalence of poor SPH was found in Peru (men = 26%; women = 34%) and Brazil (men = 21%; women = 25%), while the lowest was found in Spain (men = 9%; women = 12%) and Ecuador (men = 12%; women = 18%). There was a higher prevalence of poor SPH among those who reported belonging to indigenous groups, except for indige- nous women in Peru and indigenous men in Chile (Table 2). In Chile, Mexico, and Spain, SPH worsened with increased age, while no gradient was observed in the other countries (Figure 1a). Int. J. Environ. Res. Public Health 2023, 20, 5722 6 of 23 Table 1. Sociodemographic characteristics and variables related to social factors of the participants by sex in Brazil, Chile, Ecuador, Mexico, Peru, and Spain during the first wave of COVID-19 lockdown. Brazil Chile Ecuador México Peru Spain n = 13,943 (35.75%) n = 5612 (14.39%) n = 2653 (6.8%) n = 8396 (21.52%) n = 1122 (2.88%) n = 7280 (18.66%) Men Woman Men Woman Men Woman Men Woman Men Woman Men Woman n = 2917 n = 11,026 n = 2095 n = 3517 n = 853 n = 1800 n = 2648 n = 5748 n = 359 n = 763 n = 2101 n = 5179 %M %W p %M %W p %M %W p %M %W p %M %W p %M %W p Basic or bachelor’s 21.8 18.6 15.5 14.4 11.0 13.0 5.1 4.2 12.4 16.2 21.0 17.3 degree Educational level Technical ** ** ** 8.1 5.7 16.0 15.4 3.8 3.6 23.2 27.7 14.2 16.6 10.8 10.5 studies University 70.1 75.7 68.6 70.2 85.3 83.5 71.7 68.1 73.5 67.2 68.2 72.2 studies 18–34 32.3 27.7 28.1 31.7 41.7 55.2 44.7 48.1 39.3 50.6 23.5 27.0 Age 35–64 57.5 63.7 ** 65.1 62.3 * 54.9 43.6 ** 50.4 48.7 ** 56.3 46.1 ** 64.0 66.2 ** ≥65 10.2 8.7 6.8 6.1 3.4 1.2 5.0 3.2 4.5 3.3 12.5 6.8 Indigenous group No 66.1 68.5 89.3 90.4 90.3 93.0 89.5 90.0 83.3 85.8 membership 1 * * Yes 33.9 31.5 10.8 9.6 9.7 7.0 10.5 10.0 16.7 14.2 Born in country of 97.6 98.2 91.8 92.2 94.8 96.3 97.9 98.4 96.7 96.5 90.8 90.7 Country of origin study * Migrant 2.4 1.8 8.2 7.8 5.2 3.7 2.1 1.7 3.3 3.5 9.2 9.3 Pre-pandemic Employed 66.5 56.9 88.1 78.8 82.3 73.8 70.2 62.7 83.2 68.9 71.9 70.4 employment ** ** ** ** ** status Unemployed 33.5 43.1 11.9 21.2 17.7 26.2 29.8 37.3 16.8 31.1 28.2 29.6 No change/ improvement Change in in 47.7 49.7 41.5 44.3 30.2 28.2 49.6 47.8 48.3 47.1 59.6 59.3 employment employment status during the condition * pandemic Worsening in employment 52.3 50.3 58.5 55.7 69.8 71.8 50.4 52.3 51.8 52.9 40.4 40.7 condition Own home 67.3 68.7 58.1 57.7 64.2 65.0 63.0 61.5 59.1 61.2 69.6 71.8 Lease or rent 21.1 23.7 32.1 30.8 28.4 26.5 24.5 21.7 29.9 26.2 26.4 25.0 Housing tenure ** ** Living in someone else’s 5.6 6.7 9.8 11.5 7.5 8.5 12.5 16.8 11.0 12.6 4.0 3.3 home Int. J. Environ. Res. Public Health 2023, 20, 5722 7 of 23 Table 1. Cont. Brazil Chile Ecuador México Peru Spain n = 13,943 (35.75%) n = 5612 (14.39%) n = 2653 (6.8%) n = 8396 (21.52%) n = 1122 (2.88%) n = 7280 (18.66%) Men Woman Men Woman Men Woman Men Woman Men Woman Men Woman n = 2917 n = 11,026 n = 2095 n = 3517 n = 853 n = 1800 n = 2648 n = 5748 n = 359 n = 763 n = 2101 n = 5179 %M %W p %M %W p %M %W p %M %W p %M %W p %M %W p Suitable for 81.7 81.8 84.9 87.7 86.8 86.4 79.4 77.2 81.9 75.8 89.9 90.0 confinement Perception of adequate housing Not suitable 0 * * for 18.3 18.2 15.1 12.3 13.2 13.6 20.6 22.8 18.2 24.3 10.1 10.0 confinement Living alone 19.0 17.4 12.5 11.3 11.8 8.6 11.6 9.1 8.6 6.7 19.3 17.7 Household composition Living with * ** 81.0 82.6 87.5 88.7 88.2 91.4 88.4 90.9 91.4 93.3 80.7 82.3 other people Presence of No 67.8 62.5 56.4 55.1 50.1 47.9 53.8 48.4 42.0 37.3 70.0 64.3 minors in ** ** ** the household Yes 32.2 37.5 43.6 44.9 49.9 52.1 46.2 51.6 58.0 62.7 30.0 35.7 Presence of No 43.0 43.2 64.8 59.8 58.4 48.6 62.7 51.9 48.0 43.4 87.9 84.8 dependents in the ** ** ** ** household Yes 57.1 56.8 35.2 40.2 41.6 51.4 37.4 48.1 52.0 56.6 12.1 15.2 Other per- sons/equally among 84.0 48.4 87.5 55.2 89.1 65.0 88.8 66.3 90.8 70.0 Household work household ** ** ** ** ** members Mostly by 15.9 51.6 12.5 44.8 10.9 35.0 11.2 33.7 9.3 30.0 myself Nothing or Concern about 30.9 32.2 46.2 51.3 42.8 44.7 48.0 49.9 36.2 37.0 79.6 76.2 little living with household Moderate, ** * members quite a bit, or a 69.1 67.8 53.3 48.8 57.2 55.3 52.0 50.1 63.8 63.0 20.4 23.9 lot Nothing or 17.6 22.0 32.6 41.1 13.9 13.0 26.6 27.0 24.9 26.3 43.6 51.5 little Concern about schooling Moderate, ** ** ** quite a bit, 82.4 78.0 67.4 48.9 86.1 87.0 73.4 73.0 75.1 73.8 56.4 48.5 or a lot % M = percentage of men; % W = percentage of women. 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous). p = statistical significance between men and women derived from the chi-squared test; ** p < 0.001, * p < 0.05. NA: not applicable (no information on this variable). Int. J. Environ. Res. Public Health 2023, 20, 5722 8 of 23 Table 2. Prevalence of self-perceived poor health according to gender and sociodemographic characteristics in Brazil, Chile, Ecuador, Mexico, Peru, and Spain during the first wave of COVID-19 lockdown. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2526 N = 9739 N = 1928 N = 3288 N = 759 N = 1637 N = 2405 N = 5320 N = 323 N = 688 N = 2092 N= 5162 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Self-perceived health 21 (19–22) 25 (24–25) 17 (15–18) 22 (20–23) 12 (10–15) 18 (16–19) 16 (14–17) 21 (20–22) 26 (21–31) 34 (31–38) 9 (8–11) 12 (11–13) Basic or bachelor’s 29 (25–33) 37 (35–39) 24 (19–28) 34 (30–38) 20 (11–28) 21 (15–26) 24 (16–31) 34 (28–40) 35 (20–50) 36 (27–45) 12 (9–15) 20 (18–23) degree Educational level Technical studies 25 (19–31) 35 (31–39) 23 (18–27) 29 (25–33) 07 (0–17) 30 (18–42) 19 (16–23) 26 (23–28) 22 (9–35) 32 (23–40) 12 (7–16) 16 (12–19) University studies 18 (16–20) 21 (20–22) 14 (12–15) 18 (16–19) 11 (9–14) 16 (15–18) 14 (13–16) 18 (17–20) 26 (20–31) 34 (30–38) 8 (7–10) 10 (9–11) 18–34 22 (19–25) 25 (24–27) 17 (13–20) 20 (18–23) 13 (9–17) 18 (15–20) 15 (13–17) 19 (17–20) 24 (16–32) 27 (23–32) 4 (2–6) 9 (7–10) Age 35–64 20 (18–22) 25 (23–26) 16 (14–18) 22 (20–23) 12 (9–15) 18 (15–20) 16 (14–18) 23 (21–25) 26 (20–33) 41 (36–47) 11 (9–12) 13 (12–15) ≥65 18 (14–23) 23 (21–26) 23 (16–30) 28 (22–35) 07 (0–17) 09 (0–22) 26 (18–34) 27 (20–33) 38 (12–65) 35 (15–54) 12 (08–16) 13 (10–17) Indigenous group No 19 (17–21) 22 (21–23) 17 (15–19) 21 (20–23) 11 (9–13) 16 (14–18) 15 (14–17) 21 (20–22) 23 (18–28) 34 (30–38) NA NA membership 1 Yes 23 (20–26) 31 (29–33) 16 (11–21) 27 (22–32) 25 (15–35) 36 (27–44) 19 (14–24) 23 (20–27) 40 (27–54) 33 (24–43) NA NA Born in the 21 (19–22) 25 (24–26) 17 (15–19) 22 (21–24) 12 (9–14) 18 (16–19) 16 (14–17) 21 (20–22) NA NA 9 (7–10) 12 (11–13) Country of origin country of study Migrant 24 (13–35) 23 (17–29) 13 (06–19) 13 (08–18) 21 (8–33) 17 (8–27) 10 (2–18) 14 (7–21) NA NA 14 (10–19) 15 (12–18) Pre-pandemic Employed 19 (17–21) 22 (21–24) 15 (14–17) 19 (17–20) 11 (9–14) 17 (15–19) 15 (14–17) 21 (19–22) 26 (20–31) 35 (30–39) 8 (7–9) 9 (8–10) employment status, Unemployed 24 (21–27) 26 (25–28) 23 (18–29) 30 (26–33) 16 (9–22) 19 (15–23) 17 (14–19) 22 (20–24) 27 (15–39) 33 (26–39) 13 (10–16) 19 (17–21) No change/improvement Change in 18 (15–20) 22 (21–23) 13 (11–15) 18 (16–20) 9 (5–13) 15 (12–18) 13 (12–15) 18 (17–20) 18 (12–25) 29 (24–35) 10 (8–12) 12 (10–13) in employment employment condition status during the pandemic Worsening in employ–ment 23 (21–26) 28 (26–29) 19 (17–22) 24 (23–26) 13 (11–16) 19 (16–21) 18 (16–20) 24 (22–25) 35 (27–42) 38 (33–44) 9 (7–11) 13 (12–15) condition Own home 19 (17–21) 23 (22–24) 16 (13–18) 19 (17–21) 10 (7–13) 16 (14–18) 15 (14–17) 19 (18–21) 25 (19–31) 33 (28–37) 10 (8–12) 12 (11–13) Housing tenure Lease or rent 22 (19–25) 27 (25–29) 17 (14–19) 23 (21–26) 17 (12–22) 20 (16–24) 15 (12–18) 21 (18–23) 27 (18–36) 31 (24–38) 7 (5–10) 11 (9–13) Living in someone 32 (24–40) 38 (34–41) 24 (18–31) 29 (25–34) 14 (5–23) 21 (15–28) 19 (15–24) 28 (25–31) 31 (16–46) 45 (35–56) 08 (2–14) 19 (13–24) else’s home Int. J. Environ. Res. Public Health 2023, 20, 5722 9 of 23 Table 2. Cont. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2526 N = 9739 N = 1928 N = 3288 N = 759 N = 1637 N = 2405 N = 5320 N = 323 N = 688 N = 2092 N= 5162 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Suitable for 18 (16–20) 22 (21–23) 15 (13–17) 19 (18–21) 10 (8–12) 16 (14–18) 15 (13–16) 19 (17–20) 23 (18–28) 32 (28–36) 9 (8–10) 11 (10–12) Perception of confinement adequate housing Not suitable for confinement 31 (27–35) 37 (35–40) 27 (22–32) 38 (33–43) 26 (18–35) 29 (23–35) 20 (17–24) 30 (27–33) 42 (29–55) 42 (34–49) 14 (9–18) 20 (16–23) Living alone 20 (17–24) 23 (21–25) 15 (11–20) 18 (14–22) 14 (7–21) 15 (9–21) 17 (12–21) 17 (14–20) 14 (01–26) 22 (10–34) 10 (07–13) 12 (10–14) Household composition Living with 21 (19–22) 25 (24–26) 17 (15–19) 22 (21–24) 12 (10–14) 18 (16–20) 16 (14–17) 22 (20–23) 27 (22–32) 35 (31–39) 9 (8–10) 12 (11–13) other people Presence of No 20 (18–22) 24 (23–25) 18 (15–20) 22 (20–25) 12 (9–16) 15 (12–17) 16 (13–18) 20 (18–21) 31 (22–40) 32 (25–38) 10 (6–13) 15 (12–17) minors in the household, Yes 21 (19–24) 26 (24–27) 16 (14–19) 22 (20–24) 12 (8–15) 20 (18–23) 16 (14–18) 23 (21–25) 25 (19–31) 37 (32–41) 6 (3–08) 9 (7–11) Presence of No 17 (14–20) 21 (19–22) 13 (11–15) 19 (17–21) 12 (8–15) 12 (10–15) 12 (10–13) 16 (14–17) 22 (15–30) 27 (21–32) 17 (11–23) 16 (12–19) dependents in the household Yes 22 (20–24) 27 (26–28) 23 (20–26) 26 (24–29) 12 (9–16) 22 (19–25) 21 (19–24) 27 (25–28) 31 (24–38) 40 (35–45) 9 (4–15) 13 (9–17) Other persons/equally among household 20 (18–22) 23 (22–25) 17 (15–19) 20 (18–22) 12 (10–15) 16 (14–18) 15 (14–17) 20 (18–21) 27 (22–32) 31 (27–35) NA NA Household work members Mostly by myself 24 (19–29) 26 (25–28) 18 (13–24) 24 (22–26) 11 (4–18) 21 (18–25) 19 (14–24) 25 (23–27) 30 (12–47) 45 (38–52) NA NA Concern about Nothing or little 14 (12–17) 19 (18–21) 13 (11–15) 19 (17–21) 9 (6–13) 13 (10–16) 13 (11–15) 19 (17–20) 19 (12–27) 26 (21–32) 8 (7–10) 10 (9–11) living with household Moderate, quite a 23 (21–26) 28 (26–29) 20 (18–23) 25 (23–28) 14 (10–17) 22 (19–24) 18 (16–20) 24 (23–26) 32 (25–39) 40 (35–45) 13 (9–16) 18 (16–21) members bit or a lot Nothing or little 26 (19–33) 22 (19–25) 17 (13–22) 20 (16–23) 11 (3–20) 14 (8–21) 16 (12–20) 21 (18–24) 14 (03–24) 30 (21–38) 6 (3–9) 10 (8–11) Concern about schooling Moderate, quite a 21 (18–24) 27 (25–29) 16 (13–19) 23 (20–26) 12 (8–15) 21 (18–24) 16 (13–18) 24 (22–26) 27 (20–35) 39 (34–45) 9 (6–11) 14 (12–16) bit or a lot NA: not applicable (no information on this variable). 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous). Int. J. Environ. Res. Public Health 2023, 20, 5722 10 of 23 Figure 1. Prevalence of (a) self-perceived poor health, (b) anxiety, and (c) depressive symptoms according to age and gender in Brazil, Chile, Ecuador, Mexico, Peru and Spain in the first wave of COVID-19 lockdown. In most cases there was a higher prevalence of poor SPH among those who were not employed, and it was higher in women in all countries (except Peru). Among those in paid employment, poor SPH was related to worsening employment status, especially among women in Peru. For home tenure, there was a gradient in the prevalence of poorer SPH across countries, with a lower prevalence among those living in their own home, a higher prevalence among those living in rented houses, and an even higher prevalence among those living in someone else’s home. The highest prevalence was reported among women living in someone else’s home in Peru (45%) and Brazil (38%) (Table 2). Regarding family composition and unpaid care work, there were no clear trends between the number of household members and the presence of children. However, there was a higher prevalence of poorer SPH in those living with dependents in all countries for both genders (except men in Ecuador), being higher in women in Peru (40%), Brazil (27%), and Mexico (27%). In addition, there was a higher prevalence of poor SPH among those who performed most of the housework in the home, especially among women in Peru (45%). Regarding concern for household members and their school education, there was a higher prevalence of poor SPH for those who reported worrying a great deal or a lot in all countries studied, being higher in women from Peru (39%) and Brazil (27%) (Table 2). 3.2. Mental Health: Anxiety and Depression The highest prevalence of mental health problems was found in Chile (anxiety: men = 43%, women = 58%; depression: men = 31%, women = 42%) and Ecuador (anxiety: men = 35%, women = 46%; depression: men = 32%, women = 43%), and the lowest preva- lence was found in Spain (anxiety: men = 18%, women = 31%; depression: men = 16%, women = 28%). There was a higher prevalence of anxiety and depressive symptoms in women regardless of country and sociodemographic characteristics. The highest prevalence of anxiety and depression was observed in the younger groups, decreasing in the older groups in all countries (Figure 1b,c). A higher prevalence of anxiety and depression was observed in women belonging to indigenous groups (Tables 3 and 4). Int. J. Environ. Res. Public Health 2023, 20, 5722 11 of 23 Table 3. Prevalence of anxiety according to gender and sociodemographic characteristics in Brazil, Chile, Ecuador, Mexico, Peru, and Spain during the first wave of COVID-19 lockdown. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2404 N = 9307 N = 1809 N = 3167 N = 711 N = 1496 N = 2210 N = 4867 N = 299 N = 645 N = 2077 N = 5155 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Anxiety 27 (25–29) 37 (36–38) 43 (41–45) 58 (56–60) 35 (32–39) 46 (43–48) 28 (26–30) 41 (40–43) 30 (25–36) 38 (34–42) 18 (16–19) 31 (30–33) Basic or bachelor’s 33 (29–37) 46 (44–48) 51 (46–57) 69 (64–73) 44 (32–55) 48 (40–55) 31 (21–40) 42 (35–50) 40 (24–56) 52 (43–62) 18 (15–22) 38 (35–41) degree Educational level Technical studies 35 (28–41) 47 (43–51) 44 (39–50) 63 (58–67) 32 (14–50) 45 (31–59) 30 (26–34) 44 (41–46) 32 (17–46) 41 (31–50) 21 (15–26) 35 (31–39) University studies 24 (22–26) 34 (33–35) 41 (38–44) 55 (52–57) 34 (30–38) 46 (43–48) 28 (25–30) 40 (39–42) 29 (23–35) 34 (30–39) 17 (15–19) 29 (28–31) 18–34 40 (36–43) 49 (47–51) 51 (47–56) 65 (62–68) 39 (34–45) 49 (45–52) 33 (31–36) 47 (45–49) 37 (28–46) 44 (39–50) 23 (20–27) 40 (37–43) Age 35–64 24 (22–26) 34 (33–35) 42 (39–45) 56 (53–58) 33 (29–38) 43 (39–46) 25 (22–27) 36 (34–38) 26 (20–33) 32 (27–38) 17 (15–19) 29 (28–31) ≥65 9 (6–13) 19 (16–21) 18 (11–24) 42 (35–49) 20 (4–36) 28 (7–48) 14 (7–21) 25 (18–32) 31 (6–56) 30 (10–50) 9 (6–13) 15 (12–19) Indigenous group No 27 (24–29) 36 (35–37) 43 (41–46) 57 (55–59) 35 (32–39) 45 (42–47) 29 (27–31) 41 (40–42) 28 (22–33) 38 (34–42) NA NA membership 1 Yes 28 (25–31) 39 (37–40) 43 (36–50) 65 (59–70) 35 (23–47) 57 (48–67) 22 (17–28) 44 (39–48) 45 (30–59) 38 (27–48) NA NA Born in the 27 (26–29) 37 (36–38) 44 (41–46) 58 (56–60) 36 (32–39) 46 (43–48) 28 (26–30) 41 (40–43) NA NA 17 (15–19) 31 (30–33) Country of origin country of study Migrant 12 (04–21) 30 (23–38) 33 (23–42) 53 (45–61) 29 (14–44) 47 (34–60) 21 (09–32) 42 (32–53) NA NA 22 (17–27) 33 (29–36) Pre-pandemic Employed 27 (25–29) 37 (36–39) 43 (41–46) 57 (55–59) 35 (31–39) 45 (42–48) 28 (26–30) 41 (40–43) 29 (23–34) 36 (32–41) 19 (17–21) 31 (29–32) employment status, Unemployed 26 (23–30) 36 (34–38) 39 (32–45) 61 (57–65) 39 (30–47) 47 (42–53) 28 (25–32) 41 (39–43) 40 (26–54) 44 (37–51) 16 (13–18) 32 (30–35) No change/improvement Change in 17 (15–20) 29 (28–31) 35 (32–39) 52 (49–54) 24 (18–30) 36 (31–41) 21 (19–24) 34 (32–36) 22 (15–28) 32 (26–37) 15 (13–17) 27 (25–28) in employment employment condition status during the pandemic Worsening in employment 36 (33–38) 44 (42–45) 49 (46–52) 63 (61–65) 40 (36–44) 50 (47–53) 35 (32–38) 48 (46–50) 39 (31–47) 44 (38–50) 22 (19–25) 38 (36–40) condition Own home 24 (22–26) 34 (33–35) 39 (36–42) 54 (51–56) 34 (30–38) 43 (40–46) 26 (24–28) 38 (36–40) 25 (19–32) 36 (31–40) 16 (14–18) 30 (29–32) Housing tenure Lease or rent 31 (27–34) 42 (40–44) 48 (44–52) 63 (60–66) 37 (30–44) 50 (45–55) 33 (29–37) 47 (44–50) 37 (27–47) 44 (36–51) 20 (16–23) 33 (31–36) Living in someone 41 (33–49) 47 (43–51) 52 (44–59) 64 (59–69) 37 (24–50) 53 (45–62) 30 (25–36) 46 (43–50) 38 (21–54) 39 (28–49) 24 (15–33) 35 (28–42) else’s home Int. J. Environ. Res. Public Health 2023, 20, 5722 12 of 23 Table 3. Cont. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2404 N = 9307 N = 1809 N = 3167 N = 711 N = 1496 N = 2210 N = 4867 N = 299 N = 645 N = 2077 N = 5155 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Suitable for 24 (22–26) 34 (33–35) 41 (39–43) 56 (54–58) 33 (30–37) 43 (41–46) 26 (24–28) 38 (37–40) 25 (19–30) 34 (29–38) 16 (14–18) 29 (28–31) Perception of confinement adequate housing Not suitable for confinement 41 (37–46) 50 (48–53) 55 (49–61) 72 (67–76) 48 (38–59) 63 (56–70) 38 (34–43) 52 (49–55) 57 (43–70) 53 (45–61) 33 (26–39) 50 (45–54) Living alone 25 (21–28) 29 (27–31) 43 (36–49) 50 (45–55) 33 (23–42) 45 (36–53) 28 (22–33) 40 (35–44) 39 (21–57) 23 (10–35) 19 (15–23) 28 (25–31) Household composition Living with 28 (26–30) 38 (37–39) 43 (41–46) 59 (57–61) 36 (32–39) 46 (43–49) 28 (26–30) 41 (40–43) 30 (24–35) 39 (35–43) 18 (16–19) 32 (31–33) other people Presence of No 26 (24–29) 36 (34–37) 42 (39–46) 56 (54–59) 38 (32–44) 44 (40–48) 28 (25–31) 40 (37–42) 29 (20–38) 32 (25–38) 21 (16–25) 33 (30–37) minors in the household, Yes 29 (26–32) 41 (40–43) 44 (41–48) 61 (59–64) 34 (29–38) 47 (44–51) 29 (26–31) 43 (41–45) 30 (23–37) 43 (38–48) 22 (17–26) 35 (32–38) Presence of No 25 (22–29) 34 (32–35) 40 (37–43) 54 (51–56) 33 (28–38) 42 (38–46) 26 (23–28) 37 (35–39) 24 (16–32) 35 (29–41) 24 (17–32) 35 (30–39) dependents in the household Yes 28 (26–31) 40 (39–42) 48 (44–52) 65 (62–67) 38 (33–44) 49 (45–52) 32 (29–35) 46 (43–48) 34 (26–42) 42 (37–47) 26 (18–34) 42 (37–48) Other persons/equally among household 26 (24–29) 35 (34–37) 42 (39–44) 55 (53–58) 35 (31–39) 43 (40–47) 27 (25–29) 38 (37–40) 29 (23–35) 37 (32–41) NA NA Household work members Mostly by myself 33 (28–38) 41 (40–43) 55 (48–61) 64 (61–66) 40 (28–52) 51 (47–56) 38 (32–45) 47 (45–50) 35 (16–53) 45 (38–52) NA NA Concern about Nothing or little 15 (12–18) 27 (25–29) 33 (30–37) 49 (47–52) 27 (22–32) 34 (30–38) 19 (16–21) 32 (30–34) 23 (15–31) 27 (21–33) 12 (11–14) 26 (24–27) living with household Moderate, quite a 33 (31–36) 44 (42–45) 52 (49–55) 69 (67–72) 42 (37–47) 56 (52–59) 37 (34–40) 51 (49–53) 34 (27–41) 46 (41–51) 38 (32–43) 53 (50–56) members bit or a lot Nothing or little 27 (19–34) 37 (34–41) 41 (35–47) 59 (55–63) 24 (12–36) 37 (27–47) 29 (23–34) 37 (33–41) 25 (11–39) 28 (19–37) 16 (12–21) 29 (27–32) Concern about schooling Moderate, quite a 30 (26–33) 43 (41–45) 46 (41–50) 64 (61–67) 35 (30–40) 49 (45–53) 32 (29–35) 45 (43–47) 30 (22–38) 48 (42–54) 25 (20–30) 40 (37–43) bit or a lot NA: not applicable (no information on this variable). 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous). Int. J. Environ. Res. Public Health 2023, 20, 5722 13 of 23 Table 4. Prevalence of depressive symptoms according to gender and sociodemographic characteristics in Brazil, Chile, Ecuador, Mexico, Peru, and Spain during the first wave of COVID-19 lockdown. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2414 N = 9323 N = 1799 N = 3164 N = 709 N = 1493 N = 2208 N = 4865 N = 298 N = 647 N = 2074 N = 5107 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Depressive symptomns 28 (26–30) 37 (36–38) 31 (29–33) 42 (40–44) 32 (28–35) 43 (40–45) 28 (26–30) 40 (39–42) 27 (21–32) 37 (33–40) 16 (15–18) 28 (27–30) Basic or bachelor’s 36 (32–40) 47 (45–50) 46 (40–52) 60 (55–64) 44 (32–55) 61 (54–68) 31 (22–41) 40 (32–47) 37 (21–53) 58 (48–67) 18 (15–22) 35 (32–39) degree Educational level Technical studies 34 (27–41) 49 (45–54) 30 (25–35) 43 (39–48) 31 (13–49) 42 (29–56) 36 (32–40) 48 (45–51) 46 (31–62) 40 (31–50) 18 (13–23) 32 (28–36) University studies 25 (23–27) 34 (33–35) 28 (26–31) 38 (36–40) 30 (27–34) 40 (38–43) 26 (23–28) 38 (36–39) 22 (16–27) 31 (27–35) 16 (14–18) 26 (25–28) 18–34 45 (42–49) 54 (52–56) 46 (41–50) 56 (53–59) 40 (35–46) 49 (46–53) 38 (35–41) 51 (49–53) 40 (31–49) 46 (40–51) 28 (24–32) 42 (40–45) Age 35–64 23 (21–25) 33 (32–34) 28 (25–30) 36 (34–39) 26 (22–31) 36 (32–39) 21 (19–24) 31 (29–33) 18 (13–24) 29 (24–34) 14 (12–16) 24 (23–26) ≥65 8 (5–11) 18 (16–21) 7 (3–12) 25 (18–31) 25 (8–42) 22 (3–41) 7 (2–12) 16 (10–23) 23 (0–46) 05 (0–13) 06 (3–9) 13 (9–17) Indigenous group No 27 (25–29) 36 (34–37) 30 (23–36) 41 (40–43) 32 (29–36) 42 (40–45) 28 (26–30) 40 (39–42) 25 (20–30) 36 (32–40) NA NA membership 1 Yes 30 (27–33) 40 (39–42) 32 (29–34) 47 (42–53) 27 (16–39) 50 (40–59) 25 (19–31) 41 (37–45) 36 (22–50) 43 (32–54) NA NA Born in the 28 (27–30) 37 (36–38) 32 (30–34) 38 (36–39) 33 (29–36) 43 (40–46) 28 (26–30) 40 (39–42) NA NA 16 (15–18) 28 (27–29) Country of origin country of study Migrant 16 (06–25) 29 (22–36) 19 (11–27) 34 (27–42) 15 (04–27) 35 (22–47) 21 (9–32) 40 (29–50) NA NA 19 (14–24) 31 (27–35) Pre-pandemic Employed 28 (25–30) 37 (36–39) 30 (27–32) 39 (37–41) 30 (26–33) 38 (35–41) 26 (24–29) 38 (36–40) 23 (18–28) 31 (27–35) 16 (14–18) 26 (25–27) employment status, Unemployed 31 (27–34) 38 (36–39) 39 (33–46) 52 (48–56) 43 (34–51) 56 (51–61) 32 (28–36) 45 (43–47) 46 (32–60) 52 (45–59) 18 (15–21) 34 (32–36) No change/improvement Change in 19 (17–21) 29 (28–30) 25 (22–28) 35 (32–37) 22 (16–27) 34 (29–38) 22 (19–24) 32 (30–34) 19 (12–25) 28 (23–34) 13 (11–14) 24 (22–25) in employment employment condition status during the pandemic Worsening in employment 37 (34–39) 45 (44–47) 36 (33–39) 48 (46–50) 36 (32–41) 46 (43–49) 34 (32–37) 48 (46–50) 33 (25–41) 41 (35–47) 22 (19–25) 35 (33–37) condition Own home 25 (23–27) 34 (32–35) 27 (24–30) 37 (34–39) 31 (27–35) 40 (37–43) 24 (22–26) 36 (34–38) 22 (16–28) 34 (29–38) 14 (12–16) 26 (25–27) Housing tenure Lease or rent 35 (31–38) 44 (41–46) 35 (32–39) 48 (45–51) 32 (25–38) 48 (43–53) 35 (31–40) 46 (43–49) 35 (25–45) 44 (37–52) 20 (16–23) 32 (29–35) Living in someone 38 (30–46) 51 (47–55) 43 (35–50) 52 (46–57) 38 (25–51) 49 (40–57) 35 (29–41) 50 (46–53) 26 (10–41) 35 (24–45) 26 (16–35) 40 (32–47) else’s home Int. J. Environ. Res. Public Health 2023, 20, 5722 14 of 23 Table 4. Cont. Brasil Chile Ecuador Mexico Perú Spain Men Women Men Women Men Women Men Women Men Women Men Women N = 2414 N = 9323 N = 1799 N = 3164 N = 709 N = 1493 N = 2208 N = 4865 N = 298 N = 647 N = 2074 N = 5107 Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence Prevalence (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) (IC95%) Suitable for 25 (23–27) 34 (33–35) 29 (27–31) 39 (38–41) 30 (27–34) 41 (38–44) 26 (24–28) 37 (36–39) 23 (18–28) 33 (28–37) 14 (13–16) 26 (25–27) Perception of confinement adequate housing Not suitable for confinement 40 (36–45) 52 (50–55) 45 (39–51) 62 (57–67) 43 (33–54) 54 (47–61) 37 (33–42) 52 (49–55) 43 (29–56) 49 (41–57) 34 (28–41) 48 (44–52) Living alone 27 (23–31) 31 (29–33) 33 (27–40) 38 (33–43) 31 (22–41) 49 (41–58) 29 (24–35) 42 (37–46) 39 (21–57) 23 (11–36) 19 (15–23) 30 (27–33) Household composition Living with other 28 (26–30) 38 (37–39) 31 (29–33) 43 (41–44) 32 (28–36) 42 (39–45) 28 (26–30) 40 (39–42) 25 (20–30) 38 (34–41) 16 (14–18) 28 (27–29) people Presence of No 28 (25–30) 37 (35–38) 33 (30–37) 44 (42–47) 36 (30–41) 46 (42–50) 29 (27–32) 38 (36–40) 26 (18–35) 33 (26–39) 15 (11–19) 27 (24–30) minors in the household, Yes 29 (26–32) 40 (39–42) 29 (26–32) 41 (38–43) 29 (24–34) 39 (36–43) 27 (24–29) 42 (40–44) 25 (18–31) 40 (35–45) 15 (11–19) 26 (23–28) Presence of No 29 (25–33) 36 (34–37) 28 (25–30) 39 (37–42) 30 (25–35) 40 (36–44) 23 (20–25) 37 (35–39) 22 (14–29) 37 (31–43) 25 (18–32) 29 (25–33) dependents in the household Yes 28 (26–31) 40 (38–41) 36 (32–40) 47 (44–50) 34 (28–39) 44 (40–47) 25 (22–28) 43 (41–45) 28 (21–35) 38 (33–43) 17 (10–25) 28 (23–33) Other persons/equally among household 26 (24–29) 37 (35–38) 29 (27–31) 40 (38–43) 32 (28–35) 42 (39–45) 27 (25–29) 39 (38–41) 24 (19–30) 36 (31–40) NA NA Household work members Mostly by myself 39 (34–44) 40 (38–41) 45 (38–52) 45 (43–48) 35 (23–46) 43 (38–47) 38 (32–45) 42 (40–45) 35 (16–53) 42 (35–49) NA NA Concern about Nothing or little 19 (16–23) 30 (28–31) 24 (21–27) 33 (31–36) 27 (22–32) 32 (28–36) 21 (18–23) 34 (32–36) 19 (11–27) 27 (21–33) 12 (10–13) 22 (20–23) living with household Moderate, quite a 32 (30–35) 42 (41–44) 37 (34–40) 53 (50–55) 36 (31–41) 50 (47–54) 35 (32–38) 47 (45–49) 29 (22–36) 44 (39–49) 32 (27–37) 47 (44–50) members bit or a lot Nothing or little 28 (21–36) 35 (32–39) 28 (22–33) 37 (33–41) 20 (09–31) 27 (18–36) 27 (21–32) 37 (33–41) 31 (16–45) 30 (21–39) 12 (8–16) 19 (16–21) Concern about schooling Moderate, quite a 29 (26–33) 42 (40–43) 29 (25–33) 44 (40–47) 31 (25–36) 41 (37–45) 27 (23–30) 44 (42–46) 23 (15–30) 45 (39–50) 17 (13–21) 33 (30–37) bit or a lot NA: not applicable (no information on this variable). 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous). Int. J. Environ. Res. Public Health 2023, 20, 5722 15 of 23 The prevalence of depression was higher among those who were unemployed prior to the pandemic, while it was variable for anxiety; however, it was higher in those who reported that their employment status worsened during the pandemic (for anxiety and depression), standing out women in Chile (anxiety 63%; depression 48%). The prevalence of mental health problems) increased for those who lived in rented houses and those who lived in someone else’s home. Likewise, those who considered that their housing was not adequate had a higher prevalence of mental health problems; this tendency was greater in women than in men, especially in Chile (anxiety: men = 55%, women = 72%; depression: men = 45%, women = 62%) and Ecuador (anxiety: men = 48%, women = 63%; depression men = 43%, women = 54%) (Tables 3 and 4). Regarding living together during lockdown, no clear trends were observed between the number of household members and the prevalence of anxiety and depression. Living with children was associated with higher anxiety for women in all countries, and living with dependents led to a higher prevalence of anxiety and depression. These results are consistent with the burden of care and concern about living with household members and school education for all women, with higher prevalence among women in Brazil (depression) and Chile (anxiety) (Tables 3 and 4). 4. Discussion This study showed the results of the prevalence of anxiety, depression, and SPH in Brazil, Chile, Ecuador, Peru, Mexico, and Spain during the lockdown in the first wave of the COVID-19 pandemic. Our findings highlight that there was a higher prevalence of poor SPH, especially in Peru, and a higher impact on mental health in Chile and Ecuador. Women were the most affected in all the countries studied. We observed an age gradient; younger persons had a higher presence of symptoms of anxiety and depression, but not poor SPH. Our results also suggest that there were social determinants related to a higher prevalence of poor SPH and mental health problems, especially in women, such as pre-pandemic unemployment, worse working conditions, the perception of inadequate housing, and a higher burden of unpaid care work. We observed differences in overall prevalence in our study in LA countries compared to Spain. The best results in mental health measures and SPH in Spain may indicate the relationship between the social and material circumstances in which people lived prior to the pandemic, as well as governance and its relationship with the impact on mental health. Many LA countries announced emergency fiscal plans with direct cash transfer programs to the most impoverished households, but maintaining mobility restrictions, with the subsequent loss of (mostly informal) employment and reduction in labor income, thus increasing structural inequality gaps [41]. On the other hand, in Spain, the measures were based on social welfare policies and a shorter lockdown duration, which could partly explain the lower prevalence of poor mental and SPH compared to LA countries. In this line, it is essential to consolidate universal social protection systems in LA, including social security, education, and health, which are relevant for social welfare, the effective enjoyment of rights, and the improvement of population’s health [42], especially in times of crisis and uncertainty. Moreover, it is necessary to add social sciences and women in management to be sensitive to the importance of social as continuous change, social reproduction, and gender inequalities [43,44] This study found a higher prevalence of poor SPH and mental health in all study countries among those who were unemployed, as well as among those who were working but whose employment situation worsened, as in the case for women in Peru. This result is consistent with the increase in informal work and economic fluctuations in this country [45]. In the LA context, those unemployed during the pandemic reported more stress than those employed [46]. LA and the Caribbean are the regions with the greatest impact on formal employment worldwide [17]; thus, the impact of the pandemic was related to concern about the lack of availability of material resources [46], causing uncertainty in people and damaging their mental health [47]. In addition, both Chile, immersed in a political Int. J. Environ. Res. Public Health 2023, 20, 5722 16 of 23 and institutional crisis, due to the strong discontent and social protest in response to a neoliberal model inherited from the Pinochet dictatorship [14,48], and Ecuador, which was experiencing severe economic and governmental management problems [15], had the worst mental health outcomes. Previous studies showed an association between suffering from mental health problems and living in historical contexts characterized by a lack of freedom and unstable environments [49]. On the other hand, lockdown has made the characteristics of housing and tenure relevant factors in responding to the demands of control measures. Poor SPH and mental health were lower in those who lived in their own home, while it worsened among those who live in rented houses and was further aggravated among those who lived in someone else’s home. This situation was seen in other studies, which described housing as a factor that produces stress and anxiety, when it is of poor quality, small, or perceived as inadequate to house the inhabitants of the household [50]. On the other hand, the size of the dwelling played an essential role, since it was shown that being confined to larger spaces favors SPH [14]. Another aspect not considered in these types of restrictions are the potential effects due to the energy poverty existing in the region [51], the obligation to stay in a place without good conditions (in the southern cone, autumn began on that date), and the potential effects on people’s health [52,53]. This suggests that homogeneous pandemic containment strategies fracture society and deepen existing vulnerabilities [43]. Younger people had the highest prevalence of anxiety and depression, especially in women, decreasing in older people in all countries, except for men in Peru. These results are consistent with other studies that showed a decrease in the occurrence of mental health problems with increasing age [54], despite the fact that COVID-19 threatens the physical health of the older population, related to social issues [43]. In LA, educational centers were closed for an average of more than 1 year, and, despite the boost of virtual classes, this situation increased the effects of the digital divide and emotional apathy [20]. It also increased uncertainty about daily life, as well as its financial burdens, and the continuity of learning [20], causing discomfort due to the absence of face-to-face interaction with teachers and mates [14]. On the other hand, other studies associated poor mental health in adolescents and young adults with low expectations of being able to finish their studies and the uncertainty of entering the productive world [20]. Likewise, the worst mental health outcomes in women could be explained by the negative impact of educational trajectories when there are sociopolitical and economic crises that deepen gender inequalities [55]. On the other hand, women reported that they were exhausted by having to combine caregiving, teleworking, and emotional support, with no possibility of recovery [56]. Those concerned about living with family members and school education showed a higher prevalence of poor mental health problems. This situation is framed by the crisis of care, which refers to the challenges faced by neoliberal societies to ensure social reproduc- tion, including caring for oneself and others, the time spent maintaining physical spaces, the organization of the necessary resources, and human reproduction [57]. In addition to the activity of caring itself, assuming organizational responsibilities in times of compulsory cohabitation reinforces the need to recognize and redistribute care work [58]. For this rea- son, it is imperative to establish state policies that favor co-responsibility between members of the family and social sphere, overcoming gender stereotypes. This allows us to recognize the importance of care and domestic work for the economic reproduction and wellbeing of society as one of the ways to overcome the feminization of poverty [59]. Limitations and Strengths All surveys were conducted through online tools, excluding people without access to technology and the survey itself. This may have led to an overrepresentation of responses from people with higher levels of education [60]. However, given the health context at the time of the study, this was the most convenient way to obtain the information and brings us closer to the important inequalities that exist. Another limitation was the difference in the size of the samples collected in each country. Therefore, the results should be interpreted Int. J. Environ. Res. Public Health 2023, 20, 5722 17 of 23 with caution, since the reported prevalence was not population-based, but rather referred to the social groups in our study. Among the strengths, this study is one of the first to explore the effects of lockdown in different LA countries and Spain, allowing us to have a global picture of what happened during the first wave of the pandemic, through the stratification of many sociodemographic characteristics and health outcomes. This implies considering mental health from a situated and contextual perspective, in which the strength of the state and the capacity of individuals and support networks to respond to crises are especially relevant. In future research, it would be interesting to have longitudinal studies and qualitative studies to follow the impact of the pandemic on mental health and self-perceived health over time in the region. 5. Conclusions In Latin America and Spain, the social and health crisis generated by the first wave of COVID-19 has not affected all countries and social groups equally. The impact of lockdown has particularly affected women and young people. Chile and Ecuador had the worst men- tal health outcomes, Peru had the worst SPH, and Spain had better results, mainly related to the difference in lockdown characteristics, the social context, and socioeconomic factors, especially those related to income (i.e., employment, work condition, and perception of adequate housing). The lack of preparedness and the adoption of a reactive approach underlie many mistakes in handling the COVID-19 pandemic. We need a vision with a proactive approach to planetary health prevention, which is suited for addressing the neglected systemic determinants of health that generate disease, inequality, and environ- mental degradation. This implies including different actors and expertise to understand the health and social crisis from a holistic point of view. This highlights, among structural determinants (such as housing conditions), the importance of conditions of social reproduc- tion and the provision of mental health treatment (specialized public mental health service). As suggested by this study, there is an urgent need today to promote community resilience strategies, with policies and interventions that protect the mental health of the population in emergencies such as COVID-19. Author Contributions: Conceptualization, T.L.-J., L.M.-P., B.B.L.-G., A.P., K.M.A.-C., A.B., A.Q.G., O.J.H.-C., M.M., M.S.A., J.R.B., O.B.-M., J.B., D.B.M., A.L.T.C. and C.J.-A.; methodology, C.S.Q., N.L.-C., T.L.-J., L.M.-P., B.B.L.-G., A.P., K.M.A.-C., A.B., A.Q.G., O.J.H.-C., M.M., M.S.A., J.R.B., O.B.- M., J.B., D.B.M., A.L.T.C. and C.J.-A.; validation, T.L.-J.; formal analysis, T.L.-J., C.S.Q. and N.L.-C.; data curation, T.L.-J.; writing—original draft preparation, C.S.Q., N.L.-C. and C.J.-A.; writing—review and editing, T.L.-J., L.M.-P., B.B.L.-G., A.P., K.M.A.-C., A.B., A.Q.G., O.J.H.-C., M.M., M.S.A., J.R.B., O.B.-M., J.B., D.B.M., A.L.T.C. and C.J.-A.; visualization, C.S.Q., N.L.-C., T.L.-J., L.M.-P., B.B.L.-G., A.P., K.M.A.-C., A.B., A.Q.G., O.J.H.-C., M.M., M.S.A., J.R.B., O.B.-M., J.B., D.B.M., A.L.T.C. and C.J.-A.; supervision, C.J.-A.; project administration, C.J.-A. All authors have read and agreed to the published version of the manuscript. Funding: The project received a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded on the call for the creation of Health Outcomes- Oriented Cooperative Research Networks (RICOR), with reference RD21/0016/ RD21/0016/0029, co-funded by the European Union—NextGenerationEU funds. Institutional Review Board Statement: The study was approved by the Research Ethics Committee of the Institut de Recerca en Atenció Primària Jordi Gol i Gurina (IDIAPJGol) (ref. REC 20/063-PCV). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Data cannot be shared publicly because of ethical restrictions. The Ethical Committee does not allow us to share the data publicly as our data contain sensitive per- sonal information and cannot be fully anonymized. Data are available from the Research Ethics Committee of the Institut de Recerca en Atenció Primària Jordi Gol i Gurina (IDIAPJGol) (contact via cei@idiapjgol.info) for researchers who meet the criteria for access to confidential data. Int. J. Environ. Res. Public Health 2023, 20, 5722 18 of 23 Acknowledgments: The authors thank all people who participated in completing the survey from the different participating countries. Joan Benach gratefully acknowledges the financial support by the ICREA under the ICREA Academia program. Conflicts of Interest: The authors declare no conflict of interest. Appendix A Table A1. Coding table and recategorization of variables. Variable Original Question Recategorization How would you say your general health is? Excellent; very • Good: excellent; very good; good Self-perceived health • Poor: fair; bad good; good; fair; bad • Normal/no anxiety: 0–10 points on During the last 2 weeks, how often have you been bothered by the scale Anxiety (GAD-7) • Moderate/severe anxiety: 11 points the following problems? or more on the scale • Minimal/mild depression: During the last 2 weeks, how often have you been bothered by 0–9 points on the scale Depressive symptoms (PHQ-9) the following problems? • Moderate/severe depression: 10 points or more on the scale What is your highest level of completed studies? No formal • Basic or bachelor’s degree Educational level education; primary education or EGB; secondary education; • Technical studies bachelor’s degree; technical formation; university education or higher • University studies • 18–34 years Age How old are you? • 35–64 years • ≥65 years • No Indigenous group membership 1 Do you consider yourself to belong to any indigenous people? • Yes • Born in the country of study Country of origin What is your country of birth? • Migrant What was your employment status before the pandemic? Employee with contract; self-employed or independent • Employed (formal or informal) Pre-pandemic employment status (quoting); informal work (without contract or without • Unemployed contributions); jobless; housework or care of dependent persons; student; retired or pensioner Has the confinement affected your employment situation in Change in employment status any way? No, it has not changed; yes, it has gotten a bit worse; • No change/improvement in during the pandemic yes, it has gotten much worse; yes, but it has not gotten worse employment condition or better; yes, it has improved a bit; yes, it has improved a lot • Worsening in employment condition What is the tenure regime of your home? Owned (fully paid); • Own home Housing tenure owned (paying mortgage); for rent (market price); renting a • Lease or rent room; other situation • Living in someone else’s home Do you think your home is suitable for confinement (space, • Suitable for confinement Perception of adequate housing temperature, light, number of rooms, etc.)? No; a little; • Not suitable for confinement moderately; quite a bit; very How many people do you live with (including yourself)? 0, 1, 2, • Living alone Household composition • Living with other people 3, 4, 5, 7, 8, 9, 10 or more Presence of minors in How many people under the age of 18 do you live with?0, 1, 2, • No the household 3, 4, 5, 7, 8, 9, 10 or more • Yes Presence of dependents in With how many people do you live in a situation of • No the household dependency? 0, 1, 2, 3, 4, 5, 7, 8, 9, 10 or more • Yes How is the burden of domestic work and/or care for minors • Other persons/equally among and/or dependent persons in the household distributed? household members Household work Equitably among all household members; I do it mostly myself; • Mostly by myself mostly done by other person(s) To what extent are you concerned about living together with • Nothing or little Concern about living with the members of your household? Not worried; a little worried; • Moderate, quite a bit, or a lot household members moderately worried; quite worried; very worried If you have minors in your care, how concerned are you about their school situation during the pandemic (tele-study, family • Nothing or little Concern about schooling organization during confinement, etc.)? Not worried at all; a • Moderate, quite a bit, or a lot little worried; moderately worried; quite worried very worried; I do not have minors in charge 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous). Int. J. Environ. Res. Public Health 2023, 20, 5722 19 of 23 Table A2. Distribution of missing values in sample in relation to main variables (self-perceived health, anxiety, and depression). Brazil Chile Ecuador Men Women Men Women Men Women N % N % N % N % N % N % Self-perceived poor health 391 13.4 1287 11.67 168 8.02 229 6.51 94 11.01 163 9.05 Anxiety 513 17.59 1719 15.59 286 13.65 352 10 143 16.74 305 16.94 Depressive symptoms 500 17.14 1692 15.35 294 14.03 352 10 144 16.86 306 16.99 Mexico Peru Spain Men Women Men Women Men Women N % N % N % N % N % N % Self-perceived poor health 243 9.18 428 7.45 36 10.03 75 9.8 9 0.43 17 0.33 Anxiety 438 16.54 881 15.33 60 16.71 118 15.42 24 1.14 64 1.24 Depressive symptoms 435 16.43 881 15.33 60 16.71 116 15.16 26 1.24 67 1.29 Table A3. Sociodemographic characteristics and related variables to social factors of the participants by sex in Brazil, Chile, Ecuador, Mexico, Peru, and Spain during the first wave of COVID-19 lockdown. Brasil Chile Ecuador México Perú Spain n =13,943 n = 5612 n = 2653 n = 8396 n = 1122 n =7280 Men Woman Men Woman Men Woman Men Woman Men Woman Men Woman n % n % n % n % n % n % n % n % n % n % n % n % Basic or bachelor’s 630 21.81 2034 18.63 311 15.45 489 14.39 88 11 222 12.96 135 5.11 241 4.22 42 12.39 117 16.18 439 20.96 891 17.25 degree Educational level Technical studies 235 8.13 621 5.69 322 16 523 15.39 30 3.75 61 3.56 614 23.23 1582 27.7 48 14.16 120 16.6 226 10.79 544 10.53 University studies 2024 70.06 8264 75.68 1380 68.55 2387 70.23 682 85.25 1430 83.48 1894 71.66 3888 68.08 249 73.45 486 67.22 1429 68.24 3730 72.22 18–34 941 32.3 3045 27.66 589 28.11 114 31.67 356 41.74 993 55.17 1183 44.68 2764 48.09 141 39.28 386 50.59 494 23.51 1398 26.99 Age 35–64 1674 57.47 7011 63.68 1363 65.06 2190 62.27 468 54.87 785 43.61 1334 50.38 2800 48.71 202 56.27 352 46.13 1345 64.02 3430 66.23 ≥65 298 10.23 954 8.66 143 6.83 213 6.06 29 3.4 22 1.22 131 4.95 184 3.2 16 4.46 25 3.28 262 12.47 351 6.78 Indigenous group No 1918 66.14 7498 68.51 1868 89.25 3180 90.44 770 90.27 1670 93.04 2369 89.46 5173 90 299 83.29 654 85.83 NA NA NA NA membership 1 Yes 982 33.86 3447 31.49 225 10.75 336 9.56 83 9.73 125 6.96 279 10.54 575 10 60 16.71 108 14.17 NA NA NA NA Born in the 2847 97.6 10829 98.21 1923 91.79 3244 92.24 809 94.84 1734 96.33 2592 97.89 5653 98.35 347 96.66 736 96.46 1908 90.81 4697 90.69 Country of origin country of study Migrant 70 2.4 197 1.79 172 8.21 273 7.76 44 5.16 66 3.67 56 2.11 95 1.65 12 3.34 27 3.54 193 9.19 482 9.31 Int. J. Environ. Res. Public Health 2023, 20, 5722 20 of 23 Table A3. Cont. Brasil Chile Ecuador México Perú Spain n =13,943 n = 5612 n = 2653 n = 8396 n = 1122 n =7280 Men Woman Men Woman Men Woman Men Woman Men Woman Men Woman n % n % n % n % n % n % n % n % n % n % n % n % Pre-pandemic Employed 1579 66.46 5015 56.86 1704 88.06 2579 78.77 659 82.27 1267 73.79 1859 70.2 3605 62.72 282 83.19 496 68.89 1506 71.85 3639 70.4 employment status. Unemployed 797 33.54 3805 43.14 231 11.94 695 21.23 142 17.73 450 26.21 789 29.8 2143 37.28 57 16.81 224 31.11 590 28.15 1530 29.6 No change/improvement 1258 47.67 4978 49.74 827 41.47 1495 44.34 239 30.21 474 28.23 1235 49.62 2611 47.75 152 48.25 290 47.08 1250 59.64 3062 59.27 Change in employment in employment status during condition the pandemic Worsening in employment 1381 52.33 5031 50.26 1167 58.53 1877 55.66 552 69.79 1205 71.77 1254 50.38 2857 52.25 163 51.75 326 52.92 846 40.36 2104 40.73 condition Own home 1742 67.34 6932 68.65 1146 58.11 1931 57.71 500 64.18 1080 64.98 1569 63.04 3363 61.5 198 59.1 428 61.21 1436 69.61 3647 71.76 Housing tenure Lease or rent 701 21.1 2355 23.66 633 32.1 1030 30.78 221 28.37 440 26.47 610 24.51 1186 21.69 100 29.85 183 26.18 544 26.37 1268 24.95 Living in someone 144 5.57 666 6.69 139 9.79 385 11.51 58 7.45 142 8.54 310 12.45 919 16.81 37 11.04 88 12.59 83 4.02 167 3.29 else’s home Suitable for 2117 81.74 8153 81.82 1673 84.88 2935 87.69 678 86.81 1438 86.42 1977 79.43 4222 77.21 275 81.85 531 75.75 1884 89.89 4655 90.04 Perception of confinement adequate housing Not suitable for 473 18.26 1812 18.18 298 15.12 412 12.31 103 13.19 226 13.58 512 20.57 1246 22.79 61 18.15 170 24.25 212 10.11 515 9.96 confinement Living alone 493 18.98 1738 17.4 247 12.51 378 11.27 92 11.78 144 8.63 289 11.61 498 9.11 29 8.63 47 6.7 404 19.33 913 17.71 Household composition Living with other 2104 81.02 8252 82.6 1728 87.49 2976 88.73 689 88.22 1524 91.37 2200 88.39 4970 90.89 307 91.37 655 93.3 1686 80.67 4243 82.29 people Presence of minors in No 1751 67.82 6204 62.46 1103 56.36 1836 55.14 387 50.13 795 47.86 1325 53.8 2627 48.38 139 41.99 261 37.29 1459 70.04 3303 64.32 the household. Yes 831 32.18 3729 37.54 854 43.64 1494 44.86 385 49.87 866 52.14 1138 46.2 2803 51.62 192 58.01 439 62.71 624 29.96 1832 35.68 Presence of dependents No 1103 42.95 4283 43.24 1266 64.79 1987 59.78 451 58.42 803 48.58 1543 62.65 2819 51.92 159 48.04 303 43.41 1824 87.9 4347 84.79 in the household Yes 1465 57.05 5622 56.76 688 35.21 1337 40.22 321 41.58 850 51.42 920 37.35 2611 48.08 172 51.96 395 56.59 251 12.1 780 15.21 Other persons/equally 1726 84.04 3913 48.4 1480 87.52 1615 55.21 596 89.09 977 65 1908 88.83 3234 66.31 265 90.75 452 69.97 NA NA NA NA Household work among household members Mostly by myself 327 15.93 4172 51.6 211 12.48 1310 44.79 73 10.91 526 35 240 11.17 1643 33.69 27 9.25 194 30.03 NA NA NA NA Concern about living Nothing or little 634 30.88 2606 32.2 780 46.18 1502 51.25 287 42.77 672 44.74 1031 48.02 2433 49.89 106 36.18 237 36.97 1340 79.57 3228 76.15 with household Moderate. quite a members 1419 69.12 5486 67.8 909 53.28 1429 48.75 384 57.23 830 55.26 1116 51.98 2444 50.11 187 63.82 404 63.03 344 20.43 1011 23.85 bit or a lot Nothing or little 139 17.62 790 21.98 968 32.56 596 41.1 53 13.91 112 13.04 298 26.58 747 26.99 44 24.86 110 26.25 271 43.57 936 51.46 Concern about schooling Moderate. quite a 650 82.38 2804 78.02 555 67.44 854 48.9 328 86.09 747 86.96 823 73.42 2021 73.01 133 75.14 309 73.75 351 56.43 883 48.54 bit or a lot NA: not applicable (no information on this variable). 1 Race/skin color self-declaration in case of Brazil (no: white; yes: black. brown. yellow. or indigenous). 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