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

Abstract

COVID-19 lockdowns greatly affected the mental health of populations and collectives. This study compares the mental health and self-perceived health in five countries of Latin America 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 variables. The prevalence of poor SPH, anxiety, and depression was calculated. The analyses were stratified by gender (men = M; women = W) and country. The data from 39,006 people were analyzed (W = 71.9%). There was a higher prevalence of poor SPH and bad mental health in women in all countries studied. Peru had the worst SPH results, while Chile and Ecuador had the worst mental health indicators. Spain had the lowest prevalence of poor SPH and mental health. The prevalence of anxiety and depression decreased as age increased. Unemployment, poor working conditions, inadequate housing, and the highest unpaid workload were associated with worse mental health 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.

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 psychological 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 [4,5,6]. 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 economic 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 employment 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) 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, 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., considering 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 according 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 dissemination 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 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 participating 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 [35,36,37,38,39,40].

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. Coding table and recategorization of variables.

Variable	Original Question	Recategorization
Self-perceived health	How would you say your general health is? Excellent; very good; good; fair; bad	Good: excellent; very good; good Poor: fair; bad
Anxiety (GAD-7)	During the last 2 weeks, how often have you been bothered by the following problems?	Normal/no anxiety: 0–10 points on the scale Moderate/severe anxiety: 11 points or more on the scale
Depressive symptoms (PHQ-9)	During the last 2 weeks, how often have you been bothered by the following problems?	Minimal/mild depression: 0–9 points on the scale Moderate/severe depression: 10 points or more on the scale
Educational level	What is your highest level of completed studies? No formal education; primary education or EGB; secondary education; bachelor’s degree; technical formation; university education or higher	Basic or bachelor’s degree Technical studies University studies
Age	How old are you?	18–34 years 35–64 years ≥65 years
Indigenous group membership 1	Do you consider yourself to belong to any indigenous people?	No Yes
Country of origin	What is your country of birth?	Born in the country of study Migrant
Pre-pandemic employment status	What was your employment status before the pandemic? Employee with contract; self-employed or independent (quoting); informal work (without contract or without contributions); jobless; housework or care of dependent persons; student; retired or pensioner	Employed (formal or informal) Unemployed
Change in employment status during the pandemic	Has the confinement affected your employment situation in any way? No, it has not changed; yes, it has gotten a bit worse; yes, it has gotten much worse; yes, but it has not gotten worse or better; yes, it has improved a bit; yes, it has improved a lot	No change/improvement in employment condition Worsening in employment condition
Housing tenure	What is the tenure regime of your home? Owned (fully paid); owned (paying mortgage); for rent (market price); renting a room; other situation	Own home Lease or rent Living in someone else’s home
Perception of adequate housing	Do you think your home is suitable for confinement (space, temperature, light, number of rooms, etc.)? No; a little; moderately; quite a bit; very	Suitable for confinement Not suitable for confinement
Household composition	How many people do you live with (including yourself)? 0, 1, 2, 3, 4, 5, 7, 8, 9, 10 or more	Living alone Living with other people
Presence of minors in the household	How many people under the age of 18 do you live with?0, 1, 2, 3, 4, 5, 7, 8, 9, 10 or more	No Yes
Presence of dependents in the household	With how many people do you live in a situation of dependency? 0, 1, 2, 3, 4, 5, 7, 8, 9, 10 or more	No Yes
Household work	How is the burden of domestic work and/or care for minors and/or dependent persons in the household distributed? Equitably among all household members; I do it mostly myself; mostly done by other person(s)	Other persons/equally among household members Mostly by myself
Concern about living with household members	To what extent are you concerned about living together with the members of your household? Not worried; a little worried; moderately worried; quite worried; very worried	Nothing or little Moderate, quite a bit, or a lot
Concern about schooling	If you have minors in your care, how concerned are you about their school situation during the pandemic (tele-study, family organization during confinement, etc.)? Not worried at all; a little worried; moderately worried; quite worried very worried; I do not have minors in charge	Nothing or little Moderate, quite a bit, or a lot

¹ Race/skin color self-declaration in case of Brazil (no: white; yes: black, brown, yellow, or indigenous).

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 differences 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. 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

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. 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
Educational level	Basic or bachelor’s degree	21.8	18.6	**	15.5	14.4		11.0	13.0		5.1	4.2	**	12.4	16.2		21.0	17.3	**
	Technical studies	8.1	5.7		16.0	15.4		3.8	3.6		23.2	27.7		14.2	16.6		10.8	10.5
	University studies	70.1	75.7		68.6	70.2		85.3	83.5		71.7	68.1		73.5	67.2		68.2	72.2
Age	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	**
	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 membership 1	No	66.1	68.5	*	89.3	90.4		90.3	93.0	*	89.5	90.0		83.3	85.8
	Yes	33.9	31.5		10.8	9.6		9.7	7.0		10.5	10.0		16.7	14.2
Country of origin	Born in country of study	97.6	98.2	*	91.8	92.2		94.8	96.3		97.9	98.4		96.7	96.5		90.8	90.7
	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 employment status	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
	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
Change in employment status during the pandemic	No change/improvement in employment condition	47.7	49.7		41.5	44.3	*	30.2	28.2		49.6	47.8		48.3	47.1		59.6	59.3
	Worsening in employment condition	52.3	50.3		58.5	55.7		69.8	71.8		50.4	52.3		51.8	52.9		40.4	40.7
Housing tenure	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
	Living in someone else’s home	5.6	6.7		9.8	11.5		7.5	8.5		12.5	16.8		11.0	12.6		4.0	3.3
Perception of adequate housing	Suitable for confinement	81.7	81.8		84.9	87.7	0	86.8	86.4		79.4	77.2	*	81.9	75.8	*	89.9	90.0
	Not suitable for confinement	18.3	18.2		15.1	12.3		13.2	13.6		20.6	22.8		18.2	24.3		10.1	10.0
Household composition	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
	Living with other people	81.0	82.6		87.5	88.7		88.2	91.4		88.4	90.9		91.4	93.3		80.7	82.3
Presence of minors in the household	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	**
	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 dependents in the household	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	**
	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
Household work	Other persons/equally among household members	84.0	48.4	**	87.5	55.2	**	89.1	65.0	**	88.8	66.3	**	90.8	70.0	**
	Mostly by myself	15.9	51.6		12.5	44.8		10.9	35.0		11.2	33.7		9.3	30.0
Concern about living with household members	Nothing or little	30.9	32.2		46.2	51.3	**	42.8	44.7		48.0	49.9		36.2	37.0		79.6	76.2	*
	Moderate, quite a bit, or a lot	69.1	67.8		53.3	48.8		57.2	55.3		52.0	50.1		63.8	63.0		20.4	23.9
Concern about schooling	Nothing or little	17.6	22.0	**	32.6	41.1	**	13.9	13.0		26.6	27.0		24.9	26.3		43.6	51.5	**
	Moderate, quite a bit, or a lot	82.4	78.0		67.4	48.9		86.1	87.0		73.4	73.0		75.1	73.8		56.4	48.5

% 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).

) (see

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	%
Educational level	Basic or bachelor’s degree	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
	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
Age	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
	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 membership 1	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
	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
Country of origin	Born in the country of study	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
	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
Pre-pandemic employment status.	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
	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
Change in employment status during the pandemic	No change/improvement in employment condition	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
	Worsening in employment condition	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
Housing tenure	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
	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 else’s home	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
Perception of adequate housing	Suitable for confinement	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
	Not suitable for confinement	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
Household composition	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
	Living with other people	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
Presence of minors in the household.	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
	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 in the household	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
	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
Household work	Other persons/equally among household members	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
	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 with household members	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
	Moderate. quite a bit or a lot	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
Concern about schooling	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
	Moderate. quite a bit or a lot	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

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).

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 indigenous women in Peru and indigenous men in Chile (

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 (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (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)
Educational level	Basic or bachelor’s degree	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)
	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)
Age	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)
	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 membership 1	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
	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
Country of origin	Born in the country of study	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)
	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 employment status,	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)
	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)
Change in employment status during the pandemic	No change/improvement in employment condition	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)
	Worsening in employ–ment condition	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)
Housing tenure	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)
	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 else’s home	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)
Perception of adequate housing	Suitable for confinement	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)
	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)
Household composition	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)
	Living with other people	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)
Presence of minors in the household,	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)
	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 dependents in the household	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)
	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)
Household work	Other persons/equally among household members	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
	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 living with household members	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)
	Moderate, quite a bit or a lot	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)
Concern about schooling	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)
	Moderate, quite a bit or a lot	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)

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).

). In Chile, Mexico, and Spain, SPH worsened with increased age, while no gradient was observed in the other countries (Figure 1a).

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 prevalence 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 (

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 (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (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)
Educational level	Basic or bachelor’s degree	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)
	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)
Age	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)
	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 membership 1	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
	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
Country of origin	Born in the country of study	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)
	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 employment status,	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)
	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)
Change in employment status during the pandemic	No change/improvement in employment condition	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)
	Worsening in employment condition	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)
Housing tenure	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)
	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 else’s home	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)
Perception of adequate housing	Suitable for confinement	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)
	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)
Household composition	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)
	Living with other people	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)
Presence of minors in the household,	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)
	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 dependents in the household	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)
	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)
Household work	Other persons/equally among household members	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
	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 living with household members	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)
	Moderate, quite a bit or a lot	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)
Concern about schooling	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)
	Moderate, quite a bit or a lot	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)

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).

and

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 (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (IC95%)	Prevalence (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)
Educational level	Basic or bachelor’s degree	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)
	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)
Age	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)
	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 membership 1	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
	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
Country of origin	Born in the country of study	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)
	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 employment status,	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)
	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)
Change in employment status during the pandemic	No change/improvement in employment condition	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)
	Worsening in employment condition	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)
Housing tenure	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)
	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 else’s home	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)
Perception of adequate housing	Suitable for confinement	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)
	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)
Household composition	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)
	Living with other people	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)
Presence of minors in the household,	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)
	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 dependents in the household	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)
	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)
Household work	Other persons/equally among household members	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
	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 living with household members	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)
	Moderate, quite a bit or a lot	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)
Concern about schooling	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)
	Moderate, quite a bit or a lot	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)

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).

).

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%) (Table 3 and Table 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) (Table 3 and Table 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 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 reproduction, 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 reason, 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 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 mental 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 environmental 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 reproduction 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.