COVID-19 Exposure and Associated Factors in Southern Brazil Students

Abstract

Coronavirus disease 2019 (COVID-19) emerged in late 2019 and was declared a pandemic from March 2020 to May 2023, profoundly affecting public health systems, economies, and daily life worldwide. University students were among the most impacted groups, facing abrupt transitions to remote learning, social isolation, and increased psychological distress due to academic and personal uncertainties. During the pandemic, few studies have been conducted with this population and so far, none have evaluated factors associated with COVID-19 infection in university students, so this study aimed to evaluate variables associated with COVID-19 infection among university students in southern Brazil. Data were collected from July to November 2020 through an online questionnaire addressing lifestyle and health, with participation from 1533 students. Among the variables analyzed, statistically significant associations with COVID-19 infection were identified for age, occupation, use of continuous medication, compliance with social distancing, and self-medication practices. Younger students (18–29 years) and those dedicated solely to studying exhibited higher infection rates. Additionally, participants who reported using continuous medication, not adhering to social distancing measures, or engaging in self-medication were significantly more likely to have contracted COVID-19. These results help outline risk profiles within the university student population and contribute to improved preparedness for future disease outbreaks. Furthermore, they underscore attitudes and behaviors that may increase vulnerability to infectious diseases, highlighting the importance of targeted health promotion and prevention strategies in this demographic.

1. Introduction

COVID-19 is an illness resulting from infection with SARS-CoV-2, a coronavirus first identified in Wuhan, Hubei Province, China, in 2019 following a rise in cases of community-acquired pneumonia of unknown cause [1]. The virus transmits via respiratory droplets and aerosols released by infected individuals, which meet the respiratory tract of healthy people, making the adoption of protective measures essential [2,3].

Measures such as wearing face masks, frequent hand and surface sanitization with alcohol, and maintaining social distancing were implemented to mitigate the transmission of the disease within the population. But, the closure of schools and universities and the application of home schooling was also necessary [4]. Thus, one of the populations most affected by the COVID-19 pandemic has been students [5,6].

In addition to the challenges of the pandemic, university students are a population already known for facing a period of adaptation when they enter university. University years are frequently demanding for students, as they involve the development of autonomy and accountability for their decisions, often coinciding with relocation from home and physical separation from family support networks [7]. During the pandemic, these difficulties may have been exacerbated and even more difficulties such as distancing from friends and family, a break in academic activities, uncertainty about the future and fear of coronavirus infection have been attributed to university students [8].

In Brazil, postgraduate students have had their academic performance affected by COVID-19 as well as psychological aspects about uncertainty and fear in the development of their work [9]. In addition, a considerable percentage of undergraduate students in southern Brazil practiced self-medication to prevent COVID-19 infection, demonstrating how the pandemic can affect student behavior [10].

Considering the significant impact of the COVID-19 pandemic on students, it is essential to investigate the risk factors associated with disease cases during the first year of the pandemic. Thus, the aim of this study was to identify risk factors associated with positive cases of COVID-19 in university students in southern Brazil.

2. Materials and Method

2.1. Study Design

A cross-sectional study was carried out using a fully online questionnaire during July to November 2020 with Southern Brazilian undergraduate students [10,11].

2.2. Sample Size

A previous list of all undergraduate students at higher education institutions was carried out for the southern states of Brazil (Paraná, Santa Catarina and Rio Grande do Sul) based on the total number enrolled obtained from the most recent census conducted in 2018 by the Instituto Nacional de Estudos e Pesquisas Educacionais Anísio Teixeira (INEP), available at https://www.gov.br/inep/pt-br/areas-de-atuacao/pesquisas-estatisticas-e-indicadores/censo-da-educacao-superior/resultados (accessed on 1 June 2020). According to the census, there were 1,428,267 undergraduate students in the region, resulting in a minimum required sample of 1152 participants estimated by the online calculator available at https://comentto.com/calculadora-amostral/ (accessed on 8 June 2020) considering a 5% margin of error, a 95% confidence level, and a heterogeneous population. To account for possible losses, an additional 10% was added, bringing the final required sample size to 1268 students.

2.3. Inclusion and Exclusion Criteria

To participate in the study, the student had to be an undergraduate student at a higher education institution in one of the three states in the southern region of Brazil, be over 18 years old and agree to take part in the research after reading the informed consent form. No student received any form of bonus for taking part in this study.

Respondents were excluded from the study if they were in high school, technical courses or any postgraduate course, if they were under the age of 18, if they lived in any other region of Brazil or the world, or if they did not accept after reading the Informed Consent Form.

2.4. Data Collection

A self-administered semi-structured questionnaire was created by the authors with questions about health, lifestyle and behavior before and during the COVID-19 pandemic. The questionnaire was indexed on the Google Forms^® platform to ensure the security required during the COVID-19 pandemic. All higher education institutions in the southern region of Brazil were listed and contacted via institutional email, and the questionnaire was also disseminated via social media.

2.5. Ethical Approvals

The research was approved by the Research Ethics Committee of the Federal University of Rio Grande (CEPAS-FURG) under approval number 4.127.866/2020. Participation was entirely voluntary, and an informed consent form was provided on the initial page of the online questionnaire. This document outlined the objectives of the study, potential risks, and the rights of the participants. Access to the questionnaire was granted exclusively to individuals who formally consented to participate.

2.6. Statistical Approach

The results are presented in relative and absolute frequencies and the associations between the dependent variable (COVID-19 diagnosis) and the independent variables (sociodemographic and clinical) were carried out using the Chi-square test.

3. Results

1553 university students made up the sample analyzed.

Table 1. Association performed by Chi-square between COVID-19 infection and sociodemographic variables (n/%).

Variables	COVID-19 Infection		p Value
	Yes	No
Age
18–29 years	162 (82.7)	25 (1.8)	<0.001
30 or more	34 (17.3)	1332 (98.2)
Gender
Female	136 (69.4)	972 (71.6)	0.554
Male	60 (30.6)	385 (28.4)
Race
Non white	36 (18.4)	247 (18.2)	0.921
White	160 (81.6)	1110 (81.8)
Graduation area
Health	74 (37.8)	580 (42.7)	0.189
Non health	122 (62.2)	777 (57.3)
Income (Real)
Until BRL 2100	42 (21.4)	351 (25.9)	0.333
Between BRL 2101-BRL 5250	87 (44.4)	541 (39.9)
Up to BRL 5251	67 (34.2)	465 (34.2)
Occupation
Full-time students	131 (66.8)	630 (46.4)	<0.001
Work/Internship	65 (33.2)	727 (53.6)

summarizes the associations between sociodemographic variables and the occurrence of COVID-19 infection, as assessed using the Chi-square test. Among the variables analyzed, age and occupation demonstrated statistically significant associations with COVID-19 infection.

Participants aged 18–29 years accounted for most COVID-19 cases (82.7%), whereas only 1.8% of non-infected individuals were in this age group (p < 0.001), indicating that younger individuals were significantly more likely to become infected. In terms of occupation, individuals who reported only studying were more frequently infected (66.8%) compared to those engaged in work or internships, who represented most of the non-infected group (53.6%) (p < 0.001).

Conversely, no statistically significant associations were observed between COVID-19 infection and gender (p = 0.554), race (p = 0.921), graduation area (p = 0.189), or income level (p = 0.333). These findings indicate that, within this sample, such variables were not significantly associated with the likelihood of contracting COVID-19.

Table 2. Association performed by Chi-square between COVID-19 infection and health and lifestyle variables (n/%).

Variables	COVID-19 Infection		p Value
	Yes	No
Having a chronic disease
Yes	83 (42.3)	481 (35.4)	0.068
No	113 (57.7)	876 (64.6)
Having depression and/or anxiety
Yes	43 (21.9)	331 (24.4)	0.476
No	153 (78.1)	1026 (75.6)
Using continuous use medicine
Yes	66 (33.7)	328 (24.2)	0.005
No	130 (66.3)	1029 (75.8)
Fulfilling social distancing
No	6 (3.0)	47 (3.5)	<0.001
Go out to work but avoid crowds and get togethers	76 (38.8)	340 (25.0)
Only go out to do essential things	114 (58.2)	970 (71.5)
Living
Alone	21 (10.7)	101 (7.4)	0.176
With friends or roommates	5 (2.6)	56 (4.1)
With family	170 (86.7)	1200 (88.4)
Realize health decrease during the Pandemic
Yes	94 (48.0)	697 (51.4)	0.401
No	102 (52.0)	660 (48.6)
Practice self-medication
Yes	70 (35.7)	162 (11.9)	<0.001
No	126 (64.3)	1195 (88.1)

presents the associations between health-related and behavioral variables and COVID-19 infection. Significant associations were found for the use of continuous medication, compliance with social distancing, and self-medication practices.

Among participants who were infected, 33% reported using continuous-use medications, compared to 24.2% of those who were not infected (p = 0.005). Compliance with social distancing was also significantly associated with infection status (p < 0.001). Those who did not practice social distancing or who continued to go out regularly were more likely to be infected, whereas individuals who left home only for essential activities were less likely to contract the virus.

Additionally, self-medication was notably more frequent among infected individuals (35.7%) compared to the non-infected group (11.9%) (p < 0.001), suggesting a potential link between informal treatment behaviors and increased exposure or risk of infection. In contrast, no statistically significant associations were observed between COVID-19 infection and having a chronic disease (p = 0.068), having depression and/or anxiety (p = 0.476), living conditions (p = 0.176), or perceived health deterioration during the pandemic (p = 0.401).

4. Discussion

The present study identified specific variables associated with a positive COVID-19 diagnosis in students during the first year of pandemic. Age emerged as a significant factor, with younger students comprising most confirmed cases. This finding diverges from previous evidence reported in a comprehensive review of the initial COVID-19 cases across multiple countries, in which the mean age of infected individuals was 43.38 ± 15.19 years (mean ± standard deviation), during the early phase of the pandemic [12]. However, according to a Swiss study, younger individuals may have been more susceptible to stressors associated with the COVID-19 pandemic, such as school closures—a factor that significantly impacted students [13]. Furthermore, students exclusively engaged in academic activities reported a higher incidence of COVID-19 compared to those who were simultaneously employed. School closures may have negatively impacted students’ lives by reducing social interactions with peers and disrupting their daily routines—effects particularly pronounced among those solely dedicated to studying. A systematic review highlights that school closures were associated with a range of adverse outcomes for students during the pandemic [14].

The use of continuous medication was also identified as a factor associated with a positive COVID-19 diagnosis. These medications are typically prescribed for the management of chronic diseases such as diabetes, hypertension, respiratory diseases such as asthma, among others, which often impair the immune system and reduce the body’s ability to respond effectively to other illnesses. As an infectious disease, COVID-19 may more easily affect individuals with compromised immune function or underlying health conditions [15]. Immune vulnerability may also result from the use of medications through self-medication practices, particularly when undertaken without supervision from qualified healthcare professionals. This association was evidenced in our study, which found a higher prevalence of COVID-19 positive cases among students who engaged in self-medication compared to those who did not [16,17]. Although self-medication may be perceived as a convenient approach to managing minor health issues, it also poses significant risks, as the inappropriate use of medications can lead to adverse effects and potential intoxication [16]. Particularly in Brazil, media outlets have contributed to the promotion of self-medication with drugs lacking scientific evidence for efficacy in the treatment or prevention of COVID-19. Such indiscriminate use of medications may pose serious health risks to individuals, including the increased susceptibility to COVID-19 infection, as observed in the present study [10,11].

Students who complied with social distancing measures had fewer cases of COVID-19 infection. Individuals who did not fully comply with public health recommendations—whether due to essential activities or participation in non-recommended leisure activities —exhibited a higher prevalence of COVID-19 positive cases. This finding aligns with public health guidelines and governmental directives that strongly advocate social isolation as an effective strategy to mitigate viral transmission. Given that SARS-CoV-2 spreads primarily through respiratory droplets and aerosols emitted by infected individuals and subsequently inhaled by others, reduced social contact was crucial in limiting the spread of the virus [15,18].

In addition to the associations found here, it should also be noted that the pandemic was a period of many changes for the entire population, but the closure of schools and universities brought severe changes for students, and this can impact on their attitudes and thoughts, contributing to the risk of becoming infected with COVID-19.

5. Conclusions

Our study identified associations between COVID-19 infection and factors including younger age, exclusive dedication to academic activities, use of continuous medication, engagement in self-medication, and inadequate adherence to social isolation measures. Based on these findings, it is possible to delineate specific risk groups and behaviors associated with COVID-19, thereby informing targeted strategies to mitigate the impact of current and future public health emergencies by focusing on identified risk profiles.

6. Limitations

This study was conducted over a brief period at the onset of the pandemic, during which many universities were still transitioning to remote learning models. Additionally, the use of a self-administered questionnaire may have introduced interpretation bias among the participants. The cross-sectional design limits the ability to establish causal relationships between variables, as data were collected at a single point in time rather than across multiple time periods. As such, it is not possible to determine whether the observed associations reflect long-term patterns or are specific to the context of the early pandemic period. Furthermore, the retrospective nature of the study may have been subject to recall bias, as participants were asked to reflect on past behaviors and experiences, which may not have been accurately remembered or reported. These methodological constraints should be considered when interpreting the findings and their generalizability. Finally, no multivariate analysis was performed, and no control for potential confounding factors was applied, which limits the strength of the observed associations.