Factors associated with adherence or hesitation to protective measures that influenced the control of COVID-19 in Brazil in the pre-vaccine era

Factors associated with adherence or hesitation to protective measures that influenced the control of COVID-19 in Brazil in the pre-vaccine era | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Factors associated with adherence or hesitation to protective measures that influenced the control of COVID-19 in Brazil in the pre-vaccine era Juliana Soares Tenório Araújo, Felipe Mendes Delpino, Heriederson Sávio Dias Moura, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4698075/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Preventive behavior is one of the main strategies to contain the spread of the coronavirus, understand the factors that influence adherence or hesitation to protective measures and the way the population behaves during a health crisis is of great importance. Aim: To analyze the factors associated with adherence to protection measures against Covid-19 in Brazil. Method: cross-sectional study, survey type online, between the period of August 2020 and February 2021. The population included in the study were Brazilians, aged 18 years or older. Non-probabilistic sampling was used to obtain the sample. The data was stored on the "Redcap" platform and analyzed in a descriptive and inferential approach. Results: The sample consisted of 1,516 people, women adopted 10% more protective measures than men, people with higher education level and higher income, within the age group between 40-59 years, were those who most adhered to the measures imposed by health agencies. Carrier of Asthma, Diabetes Mellitus, Systemic Arterial Hypertension, Obesity and smoking were factors that increased the adherence of protective measures in the fight against COVID-19. Conclusion: Being female, aged between 40 and 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19. COVID-19 Protection Measures Observational Study Pandemics Figures Figure 1 Figure 2 Introduction Severe Acute Respiratory Syndrome caused by SARS-CoV-2 emerged at the end of 2019 in Wuhan from Hubei, China, and quickly spread around the world. COVID-19 was declared an International Public Health Emergency on January 30, 2020, and on March 11 of the same year it was declared a pandemic by the World Health Organization (WHO) 1 . On February 26, 2020, in the state of São Paulo, Brazil registered the first case of the disease 2 . As June 3, 2022, COVID-19 has taken the lives of more than 6.2 million people worldwide 3 . In Brazil cases exceed the 30 million, where more than 660 thousand people died from the virus. These numbers could have been reduced if mass protection measures against COVID-19 were adopted 4 . Among the protection measures indicated by national and international organizations, non-pharmacological ones stand out, such as social distancing, hand hygiene, use of masks, cleaning and disinfection of environments, isolation of suspected and confirmed cases, and quarantine for cases of COVID-19 5 . Preventive behavior is one of the main strategies to contain the spread of the virus, especially at a time when vaccination is not yet adequately covered. Faced with a pandemic, caused by rapid viral spread among humans, it is important to understand the factors that influence people’s behavior in adherence or hesitation to protective measures and the way the population behaves during a health crisis. This understanding can help in the formulation of communication and intervention strategies aimed at minimizing the impact and dissemination of the disease. Scientific evidence reinforces the importance of adherence to protective measures in combating COVID-19 6 , however in Brazil there are still few studies with this objective, notably to highlight the factors associated with the risk behavior of the population about contracting and disseminating COVID-19. Given the above, the aim of the study was to analyze the behavior of the Brazilian population, adherence to protective measures that contributed to the lack of control and dissemination of the disease, a period in which the vaccine coverage was still incipient. Method This is a cross-sectional study, of the Survey type, conducted online between August 2020 and February 2021. The study was conducted according to the recommendations of the Strengthening the Reporting of Observational Studies in Epidemiology'' 7 . For study population was considered the general Brazilian population, who declared themselves resident in Brazil, aged 18 years or older, with access to the internet and who was willing to participate in the study. People who did not fully respond to the research instrument were excluded. For sample design, the study was based on convenient sample 8 , using the snowball technique, which is characterized by not adopting margin of error calculations, since it is a non-probabilistic method. For data collection, the survey was " COVID-19 Social Thermometer: Social Opinion ", which was developed and validated by researchers from the National School of Public Health of the New University of Lisbon (ENSP/UNL) from Portugal 9 , 10 , 11 . The adaptation of the survey to Brazil proved to be sufficiently valid and reliable for its wide application in the Brazilian population. Survey is composed of 151 fields, from multiple choice questions, in Checklist format, using Likert scale, with five possibilities for answers (totally agree, partially agree, partially disagree, totally disagree, I don´t know). The survey was developed and hosted on the Redcap platform of the University of São Paulo (USP) Ribeirão Preto campus. Redcap is a software of electronic data capture ( Electronic Data Capture – EDC) browser-based and metadata-oriented with workflow methodology for designing clinical and observational research databases 12 . The survey was available to the eligible public through the websites of the research institutions participating in the study and through emails, “WhatsApp”, social networks, media and blogs. When accessing the survey, the Term of Consent was made available (TCLE) to the study participants, with the instructions for completing and presenting the purpose of the research. From the set of variables of the questionnaire, it was considered as an outcome of interest the adoption of protection measures against COVID-19, which was evaluated by the following question: “Which Measures You Have Taken to Avoid Becoming Infected with COVID-19?” This question was evaluated continuously and included 13 answer options. The independent variables were: Age (18 to 39, 40 to 59, 60 or more), Gender (Male, Female), Schooling (Incomplete or less higher educations, Complete higher education, Postgraduate or more), Race/Color (White, Black, Brown, Yellow/Indigenous), Marital status (Married/Stable union, Single/Divorced/Discharged/Legally separated, Widowed), Have health insurance (No, Yes), Use of the Public Health System (No, Yes), Receiving a visit from the Community Health Agent (No, Yes), Receiving some government social support (No, Yes), Loss of monetary income during the pandemic (No, Yes), Smoking habit (No, Yes), Religion (some religion/ no religion), Present some chronical disease: Asthma (No, Yes), Hypertension (No, Yes), Diabetes Mellitus (No, Yes), Obesity (No, Yes). For the study descriptive and inferential analyses were performed. The descriptive occurred through the calculation of frequencies with 95% confidence intervals (95% CI). The descriptive analysis was performed considering the two research outcomes (did not adopt any measures, adopted all measures). The associations were evaluated by Poisson regression 13 and considering the cross-sectional design of the study, the measure of association was the prevalence ratio (PR), with their respective 95% CI. Crude and adjusted analyzes were performed for the variables sex (male, female), skin color (white, black, brown or yellow/indigenous), age (18 to 39 years, 40 to 59, 60 years or older), schooling (incomplete higher education or less, complete higher education, postgraduate or more) and marital status (married, separated/unmarried, widowed). The analyses were performed using Stata software, version 15.1. For the spatial analysis, all 5,568 Brazilian municipalities 14 were considered as the unit of analysis, for which the incidence and mortality rates due to COVID-19 were calculated, with the number of cases (or deaths) in the numerator, the population of the municipality as denominator and the multiplication factor per 1,000 inhabitants. The Local Bivariate Moran Index 15 indicates the degree of association (positive or negative) between the value of the variable of interest in each region and another variable in the same region, and thus it is possible to map the statistically significant values, generating a choropletic map according to its classification. In this study, spatial autocorrelation between COVID-19 incidence and mortality rates was tested with people who adopted at least one measure of protection against COVID-19. The classification can be: High-high (high values of incidence or mortality from COVID-19 with a high number of people who have adopted at least one protection measure against COVID-19), Low-low (low values of incidence or mortality from COVID-19 with low number of people who have adopted at least one protection measure against COVID-19), Low-high (low values of incidence or mortality from COVID-19 with a high number of people who have adopted at least one measure of protection against COVID-19) e High-low (high COVID-19 incidence or mortality values with low number of people who have adopted at least one protection measure against COVID-19). It is noteworthy that the high and low values are classified according to the mean values of the variables of the neighboring regions 15 . Results There were 1,516 participants from the five macro-regions of Brazil. Table 1 shows the main characteristics of these participants, general and stratified by adoption of protection measures against COVID-19. Table 1 . Description of the sample according to the adoption of protective measures against COVID-19, Brazil, 2020 - 2021 (n = 1516) Variables Frequency and IC95% Did not take any measure Frequency e 95% CI Adoption all measures Frequency e 95% CI Sex Female 73.0 70.7-75.2 15.8 13.7-18.1 84.2 81.9-86.3 Male 27.0 24.8-29.3 15.9 12.6-19.9 84.1 80.1-87.4 Age 18 - 39 years 34.6 32.1-37.1 15.6 12.6-19.1 84.4 80.9-87.4 40 - 59 years 41.8 39.2-44.4 12.2 9.8-15.1 87.8 84.9-90.2 60 or years 23.6 21.5-25.9 21.9 17.8-26.7 70.1 73.3-82.2 Education Level Incomplete higher or less 24.4 22.2-26.7 20.2 16.3-24.7 79.8 75.3-83.7 Graduated 25.2 23.0-27.5 18.7 15.0-23.0 81.3 77.0-85.0 Post graduate or more 50.4 47.8-53.0 11.5 9.4-14.1 88.5 85.9-90.6 Skin color White 68.1 65.6-70.5 15.5 13.4-17.9 84.5 82.1-86.6 Black 7.6 6.3-9.0 24.1 16.9-33.0 75.9 67.0-83.1 Brown 22.2 20.2-24.5 13.5 10.2-17.7 86.5 82.3-89.8 Yellow/Indigenous 2.1 1.5-3.0 20.0 9.3-38.0 80.0 62.0-90.7 Marital Status Married/Stable Union 47.1 44.5-49.6 14.8 12.3-17.6 85.2 82.4-87.7 Separated/Single 50.4 47.9-53.0 16.5 14.0-19.4 83.5 80.6-86.0 Widowed 2.5 1.8-3.4 19.4 9.6-35.5 80.6 64.5-90.4 Health insurance No 26.9 24.7-29.2 18.0 14.5-22.2 82.0 77.8-85.5 Yes 73.1 70.8-75.3 14.2 12.2-16.5 85.8 83.5-87.8 Use of SUS No 36.0 33.6-38.6 16.9 13.9-20.4 83.1 79.6-86.1 Yes 64.0 61.4-66.4 14.4 12.3-16.8 85.6 83.2-87.7 Most participants were female (73.0%), reported white skin color (68.1%), aged between 40 and 59 years (41.8%), single (as), divorced (as), discharged (as) or separated (as) judicially (50.4%) and had postgraduate level or more (50.4%). About 73.1% had health insurance and 64.0% used the Health Public System (SUS). It was observed that 19.1% (95%CI: 17.2 - 21.2) of the people did not adopt any protection measure against COVID-19. Figure 1 shows the application of the Local Bivariate Moran Index, which refers to the incidence rate for COVID-19 with people who have adopted at least one protection measure against COVID-19 (Fig 1 - A), there is a positive spatial association (High-high) in municipalities of all big regions of Brazil, except for the Northeast region, and negative spatial association (Low-low) in all five Brazilian big regions. Regarding the COVID-19 mortality rate with people who have adopted at least one protection measure against COVID-19 (Fig 1 – B), it was possible to observe the same pattern described earlier, with municipalities classified as High-high (positive spatial association) present in all big regions of Brazil, with the exception of the Northeast, and classified as Low-low (negative spatial association) in all five Regions of the country. Regarding the association between protective measures and sociodemographic factors, women took greater care in preventing COVID-19, and adopted protective measures 10% (95%CI: 1.05-1.15) more than men, results that remained significant even after adjustments for confounding factors (PR = 1.09; 95%CI: 1.04-1.14). In a previous studies developed in the United States, being female was considered a protective factor during the COVID-19 pandemic, since the female population has a greater adherence to the use of face masks when compared to men 16,17 . Historically, evidence shows that women tend to be more aware of their health status as well as seek care more proactively than men 18 . In the analyzes performed in this study, the age group between 40 and 59 years was the one that had the highest adherence to protection measures against COVID-19. Other studies corroborate this finding, since it has been observed that the increase in age is associated with higher morbidity and mortality, especially non-communicable chronic diseases, so that with advancing age, people are more likely to adhere to disease prevention and protection measures 16 . A study conducted in Hong Kong during the swine flu pandemic showed that older people tend to take greater precautions with their health. Already during the COVID-19 pandemic in the United States, an observational study showed that the older the age the better adherence to protective measures 16,17 . The results show that, even after adjusting for confounding factors, schooling was a protective factor against COVID-19. Those with complete higher education had a prevalence ratio of 8% (95%CI: 1.02-1.15) higher and those with postgraduate education or more 17% (95%CI: 1.11-1.24) had to adopt protective measures compared to those who had incomplete or less superior. Studies indicate that the level of education is an important factor for adherence to individual and collective protection measures since a lower level of education reflects less access to information 19 . In Saudi Arabia, the level of knowledge about COVID-19 was directly associated with school level and family income 20 . Lower education is a social vulnerability, and the most vulnerable population generally has less access to information for decision-making and less financial conditions to remain in quarantine. Thus, it can be assumed that less favored communities, with lower education, aggravated by lower income and less access to health services, suffer more from health inequities that were even more evident during the pandemic. The results indicate that people self-declared black adopted fewer protective measures when compared to people with other skin color. Although the statistical significance of the categories is not maintained after adjusting for confounding factors, it is important to point out that in Brazil there are significant socioeconomic inequalities related to ethnic-racial issues, and most Brazilians with low income, lower education and less access to health services are black 21 . In Brazil, 73% of the poor population is black 22 , it is worth noting that the average of deaths from COVID-19 in the five regions of Brazil was higher among black people, a fact that shows that this population is more exposed to being victims of the disease 21 . Then it is important to reflect that inequality is of great importance in social determinants in health and that this will reflect on how this population adheres or hesitates to protective measures 19,21 . In a meta-analysis carried out during the COVID-19 pandemic, it was found that smokers are in the risk group of those most susceptible to complications of the disease, especially those who need hospitalization 23 and this fact was widely publicized in the media, causing greater concern in this group. In the present study, it was identified that people who self-declared as smokers showed more care regarding protection against the infection of the new coronavirus when compared to people who do not have the habit of smoking. In general, the arrival of the new coronavirus in the world has also shaken global religion, because it is known that historically religion and illness have a strong relation of mutual influence. In Brazil, the conflict between "science and religion" gained notoriety, causing political and social repercussions 24 . While the world was discussing the closure of mosques, suspension of religious meetings, cults and masses, in Brazil, the Presidential Decree nº 10.292, of March 25, 2020, was published 25 , establishing that religious activities of all kinds should be regarded as essential services, thus exempt from measures of social isolation. The findings of this research showed that people with some religion adopted fewer protective measures when compared to people who defined themselves without religion, even after adjusting the confounding factors (Table 2). Table 2 . Association between adoption of protective measures and sociodemographic factors, Brazil, 2020 – 2021 Variables Prevalence ratio and 95% CI Gross results Prevalence ratio and 95% CI adjusted results Sex Male Reference Reference Female 1.10 1.05-1.15 1.09 1.04-1.14 Age 18 - 39 years Reference Reference 40 - 59 years 1.09 1.05-1.15 1.05 1.01-1.11 60 years or more 1.03 0.98-1.09 0.99 0.94-1.05 Education Level Incomplete higher or less Reference Reference Graduated 1.11 1.05-1.18 1.08 1.02-1.15 Post graduate or more 1.21 1.16-1.28 1.17 1.11-1.24 Skin color White Reference Reference Black 0.86 0.80-0.94 0.98 0.90-1.06 Brown 0.98 0.94-1.03 1.01 0.96-1.08 Yellow/Indigenous 0.95 0.82-1.09 0.96 0.83-1.10 Marital Status Married/Stable Union Reference Reference Separated/Single 0.94 0.91-0.98 0.98 0.94-1.03 Widowed 0.98 0.86-1.11 0.91 0.79-1.05 smoking No Reference Reference Yes 1.16 1.08-1.24 1.17 1.09-1.25 Religion Yes Reference Reference No 1.07 1.03-1.12 1.08 1.03-1.13 * Adjusted for sex, skin color, age, education and marital status Table 3 shows the association between the adoption of protective measures with situations of vulnerability and health services. The results showed that there was significance between the loss of income during the pandemic and adherence to protective measures, but the results lost statistical significance after adjustments to confounding factors. Similar results were found among those receiving government social support. Table 3 . Association between adoption of protection measures with situations of vulnerability and health services, Brazil, 2020 - 2021 Variables Prevalence ratio and 95% CI Gross results Prevalence ratio and 95% CI adjusted results Loss of income during the pandemic No Reference Reference Yes 0.96 0.92-0.99 0.99 0.95-1.03 government aid No Reference Reference Yes 0.86 0.81-0.91 0.95 0.89-1.02 Community health agent visit No Reference Reference Yes 0.90 0.86-0.95 0.93 0.87-0.98 Health plan No Reference Reference Yes 1.15 1.10-1.20 1.07 1.02-1.13 Use of SUS No Reference Reference Yes 1.00 0.96-1.04 1.03 0.98-1.07 * Adjusted for sex, skin color, age, education and marital status Participants who received visits from community health agents adopted fewer protective measures, even after adjusting for confounding factors (PR: 0.93; 95% CI: 0.93-0.98). Compared to those without health insurance, those who had health insurance were more likely to adhere to protective measures against COVID-19, even after adjusting for confounding factors (PR: 1.07; 95%CI: 1.02-1.13). The use of SUS showed no association with the adoption of protective measures. From a social perspective, it is possible to assume that those who have health insurance have better financial conditions and that those who receive visits from the community agents have a more unfavorable socioeconomic situation, so that adherence to social isolation, for example, would cause loss of source of income, since in Brazil, an important portion of the population works informally. This fact corroborates the findings about the lower income English population, who would like to be in isolation during the pandemic, but has this possibility decreased by up to three times in relation to the higher income segments 26 . Therefore, we emphasize the importance of income transfer policies for the portion of the population that cannot isolate themselves, as a way to expand the strategy to combat the pandemic, while minimizing the impact on social well-being. Table 4 shows the association between adherence to protective measures and carrying non-communicable chronic diseases. Being a carrier of Asthma, Diabetes Melittus, Systemic Arterial Hypertension and Obesity were factors that increased the adherence of protective measures in the fight against COVID-19, even after adjustments to confounding factors. Table 4 . Association between adoption of protective measures with chronic diseases, Brazil, 2020 - 2021 Variables Prevalence ratio and 95% CI Gross results Prevalence ratio and 95% CI adjusted results Asthma No Reference Reference Yes 1.26 1.17-1.36 1.20 1.10-1.30 Diabetes No Reference Reference Yes 1.35 1.25-1.45 1.30 1.20-1.41 Hypertension No Reference Reference Yes 1.34 1.27-1.40 1.29 1.23-1.37 Obesity No Reference Reference Yes 1.31 1.24-1.38 1.23 1.17-1.30 other diseases No Reference Reference Yes 1.22 1.15-1.29 1.15 1.08-1.22 * Adjusted for sex, skin color, age, education and marital status Although the epidemiological profile of people affected by COVID-19 is not fully understood, studies indicate that the most severe forms of infection are more likely to occur in the elderly and in individuals with comorbidities 23 . In addition, mortality is also significantly higher among the elderly with pre-existing health conditions, such as systemic arterial hypertension, cardiovascular diseases and diabetes mellitus 27 . Several studies have reported that patients with chronic diseases have more unfavorable outcomes regarding hospitalizations and mortality 23 , and data from information systems in the country confirm this evidence. In the study "Social Barometer in Portugal", the elderly and those with chronic diseases considered themselves at high risk of developing a severe course of the disease in case of COVID-19 infection 9 . This self-perception of risk is considered a protective factor, since those who consider themselves more likely to have complications from the disease tend to protect themselves more. In Brazil, these diseases affect almost half of people aged 65 years or older (44.6%), population vulnerable to COVID-19, namely due to age-related fragility and immune system decline. In fact, morbidity seems to be the strongest determinant of the perception of risk of becoming ill and presenting complications resulting from the disease, which consequently increases adherence to protective measures. The plausible risk of worsening COVID-19 has been widely reported by the media, medical societies, public health institutes, health authorities and patient organizations. Therefore, it is not surprising that people with comorbidities were particularly concerned about the risk of developing severe outcomes after COVID-19. This study evaluated the adherence of measures to protect the Brazilian population during the COVID-19 pandemic in the country. Data were collected at the first moment of the pandemic, where isolation measures were more restrictive, vaccination was restricted to priority groups (health professionals and the elderly), and much misinformation circulated. The results show that almost one fifth of the sample did not adopt any measures to protect themselves from the new coronavirus, and that sociodemographic determinants and the presence of chronic diseases are associated with preventive behaviors. Other pandemics have occurred in history, some with repeated cycles for centuries, such as smallpox and measles, or for decades, such as cholera. Influenza pandemics by H1N1, H2N2, H3N3 and H5N1, known respectively as "Spanish flu", "Asian flu", "Hong Kong flu" and "avian flu", however, the COVID-19 numbers are alarming. In just over two years of the new coronavirus pandemic, there are already more than 530 million confirmed cases in the world, especially Brazil, which is in 3rd place in the ranking of cases, surpassing the range of 31 million infected people, lagging only the United States and India 3 . Such numbers may be associated with the low adherence of the population to protection measures against COVID-19, which may have been triggered by the little government investment in health education actions, as well as, by economic pressures against the measures of isolation and social distancing 6 . Understanding how the population protects itself and what factors are considered protective is part of the process for formulating strategies to contain the virus. Being female, aged 40 to 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19. Although the present study sought to obtain a representative sample of the Brazilian population, the method used, as a convenience sample in the online modality, represented a limitation of the study. When it comes to online research, individuals with higher education are the most involved, a fact that can be observed in research with this characteristic approach observed in this study 28,29 . The difficulty of access to the internet, as well as the restricted access to some social layers has already been cited in the literature as a research bias, since the possibility that the participants of the research were composed mainly of people with high level of education and higher income, as already demonstrated in other studies 30 . Even in the face of the social vulnerability that the pandemic has generated in the country, a key point for its confrontation is the adhesion of protective measures. The survey data showed that most respondents are contributing to this purpose. This refers to the urgency of social protection measures and financial support, primarily for the most vulnerable social segments. It is suggested in future studies, the continuity of this with isonomy of the sample contemplating the greatest social diversity, since the method used excluded an important portion of the population that did not have access to the online survey. Certainly, a methodological design that includes follow-up or longitudinal measures is important for monitoring the behavior of all segments of the population and at all stages of the pandemic. Declarations Ethics approval and consent to participate. The study was approved by the Research Ethics Committee of the School of Nursing of Ribeirão Preto at the University of São Paulo, under protocol number CAAE: 57933622.4.1001.5393. Informed Consent Informed Consent was obtained from all the participants involved in the study. Consent for publication All the material is owned by the authors and/or no permissions are required. The authors agree and consent that if the manuscript is accepted for publication, all copyright is transferred to the journal. Availability of data and material Not applicable Competing interests I declare that the authors have no competing interests as defined by Discover Social Science and Health, or other interests that might be perceived to influence the results and/or discussion reported in this paper. Funding This study was sponsored by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001 Process: 88887.657730/2021-00 - Programa Impactos CAPES and by São Paulo State Research Support Foundation (FAPESP) grant number 2021/08263-7. Post-doctoral fellowship (FAPESP process - 2022/03964-0); CNPQ (Research Productivity Scholarship - Process Processo: 307014/2022-3). Authors' contributions I declare that the authors Araújo, JST participated in the design and writing of the manuscript. Delpino,FM participated in the statistical analysis of the study, Nascimento, CM participated as the second reviewer of the article and writing of the manuscript. Moura,HSD; Ramos, ACV; Berra TZ; Soares,DA participated in the revision of the studies. Arcêncio RA, participated in the writing and revision of the final version of the articleAll authors reviewed and approved the final version to be published, assuming responsibility for all aspects of the work, including ensuring its accuracy and integrity. Acknowledgements Not applicable Availability of data and materials I declare that all data used can be accessed References OPAS. OMS declares public health emergency of international importance by outbreak of new coronavirus - OPAS/OMS | Organização Pan-Americana da Saúde. 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P., Gir, E., & Silva, A. C. de O. e. ( 2021 ). Medidas não farmacológicas para prevenção da covid-19 entre a população idosa brasileira e fatores associados. Estudos Interdisciplinares Sobre O Envelhecimento, 26(2). https://doi.org/10.22456/2316-2171.110117 Haischer, M. H., Beilfuss, R., Hart, M. R., Opielinski, L., Wrucke, D., Zirgaitis, G. & Hunter, S. K. ( 2020 ). Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic. Plos one, 15(10) doi: 10.1371/journal.pone.0240785. Hearne, B. N., & Niño, M. D. ( 2021 ). Understanding how race, ethnicity, and gender shape mask-wearing adherence during the COVID-19 pandemic: evidence from the COVID impact survey. J Racial Ethn Health Disparities, 1-8. doi: 10.1007/s40615-020-00941-1 Oliveira, B. L. C. A. de, Thomaz, E. B. A. F. e S, Raimundo A. The association between skin color/race and health indicators in elderly Brazilians: a study based on the Brazilian National Household Sample Survey ( 2008 ). Cadernos de Saúde Pública [online]. 2014, v. 30, n. 7 [Acesseced August 11, 2022] , pp. 1438-1452. Available: . ISSN 1678-4464. https://doi.org/10.1590/0102-311X00071413. Alahdal, H., Basingab, F., Alotaibi, R. An analytical study on the awareness, attitude and practice during the COVID-19 pandemic in Riyadh, Saudi Arabia. J Infect Public Health. 2020 Oct;13(10):1446-1452. doi: 10.1016/j.jiph.2020.06.015. Epub 2020 Jun 17. PMID: 32563674; PMCID: PMC7832465. . Sthel, F.G., Silva, L.S. A crise da pandemia da COVID-19 desnuda o racismo estrutural no Brasil. Revista da Associação Portuguesa Portuguesa de Sociologia.2021 DOI: https://doi.org/10.30553/sociologiaonline.2021.26.1 Instituto Brasileiro de Geografia e Estatística (IBGE). 2020 [Internet]. Censo demográfico. [Accessed 2020 May 22]. Available: https://cidades.ibge.gov.br/brasil Emami, A., Javanmardi, F., Pirbonyeh, N., Akbari, A. Prevalence of Underlying Diseases in Hospitalized Patients with COVID-19: a Systematic Review and Meta-Analysis. Arch Acad Emerg Med. 2020 Mar 24;8(1):e35. PMID: 32232218; PMCID: PMC7096724. Carletti, A. Nobre, F. A Religião Global no Contexto da Pandemia de Covid-19 e como implicações político-religiosas no Brasil. Revista Brasileira de História das Religiões, 2021 . Brasil,2020. DECRETO Nº 10.292, DE 25 DE MARÇO DE 2020. Altera o Decreto nº 10.282, de 20 de março de 2020, que regulamenta a Lei nº 13.979, de 6 de fevereiro de 2020, para definir os serviços públicos e as atividades essenciais . Available: https://www2.camara.leg.br/legin/fed/decret/2020/decreto-10292-25-marco-2020-789872-publicacaooriginal-160178-pe.html Atchison, C., Bowman, L.R., Vrinten, C., Redd, R., Pristerà, P., Eaton, J., Ward H. Early perceptions and behavioural responses during the COVID-19 pandemic: a cross-sectional survey of UK adults. BMJ Open. 2021 Jan 4;11(1):e 043577. doi: 10.1136/bmjopen-2020-043577. PMID: 33397669; PMCID: PMC7783373. Étard, J-F., Vanhems, P., Atlani-Duault, L., Ecochard R. Potential lethal outbreak of coronavirus disease (COVID-19) among the elderly in nursing homes and long-term facilities, France, 2020 March. , 2020;25(15):pii=2000448. https://doi.org/10.2807/1560-7917.ES.2020.25.15.2000448 Szwarcwald, C. L. et al . ConVid - Behavior Survey by the Internet during the COVID-19 pandemic in Brazil: Conception and application methodology. Cad. Saude Publica 37, e00268320 ( 2021 ). Faleiros, F. et al. Use of virtual questionnaire and dissemination as a data collection strategy in scientific studies. Texto & Contexto - Enfermagem [online]. 2016, v. 25, n. 04 [Accessed August 11 2022], e3880014. Available: . Epub 2016 Out 24 . ISSN 1980-265X. https://doi.org/10.1590/0104-07072016003880014 Bazán, P. R. et al. COVID-19 information exposure in digital media and implications for employees in the health care sector: findings from an online survey. Einstein Sao Paulo Braz . 18, eAO6127 ( 2020 ). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4698075","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":337687008,"identity":"cea743a9-a3a3-454b-a79b-584676f40d25","order_by":0,"name":"Juliana Soares Tenório Araújo","email":"data:image/png;base64,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","orcid":"","institution":"University of São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Juliana","middleName":"Soares Tenório","lastName":"Araújo","suffix":""},{"id":337687009,"identity":"2f4980a8-d534-44db-9e59-ff0da4942e39","order_by":1,"name":"Felipe Mendes Delpino","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Felipe","middleName":"Mendes","lastName":"Delpino","suffix":""},{"id":337687010,"identity":"f4e44b63-f1bd-4d81-a220-abcfb323e317","order_by":2,"name":"Heriederson Sávio Dias Moura","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Heriederson","middleName":"Sávio Dias","lastName":"Moura","suffix":""},{"id":337687011,"identity":"553dcdcc-fb9a-4780-8546-bd80713fc443","order_by":3,"name":"Murilo César Nascimento","email":"","orcid":"","institution":"University of Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Murilo","middleName":"César","lastName":"Nascimento","suffix":""},{"id":337687012,"identity":"0fcd8639-931f-4d8e-87a0-ddb388e52ac7","order_by":4,"name":"Thaís Zamboni Berra","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Thaís","middleName":"Zamboni","lastName":"Berra","suffix":""},{"id":337687013,"identity":"1ff1e0f3-0d22-48c7-b7fe-06b328ae4e1a","order_by":5,"name":"Antônio Carlos Vieira Ramos","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Antônio","middleName":"Carlos Vieira","lastName":"Ramos","suffix":""},{"id":337687014,"identity":"81c75694-526f-40a2-a4d3-f50acdb43c0a","order_by":6,"name":"Débora Almeida Soares","email":"","orcid":"","institution":"NOVA – UNL. Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Débora","middleName":"Almeida","lastName":"Soares","suffix":""},{"id":337687015,"identity":"1d7d161b-c74a-438d-a0c8-68a3d1f21b71","order_by":7,"name":"Ricardo Alexandre Arcêncio","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Ricardo","middleName":"Alexandre","lastName":"Arcêncio","suffix":""}],"badges":[],"createdAt":"2024-07-06 20:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4698075/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4698075/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62283832,"identity":"8d800b24-5847-432a-bd5a-0c69f022e909","added_by":"auto","created_at":"2024-08-12 13:04:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77810,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4698075/v1/5b8219c36db97501ca590714.jpg"},{"id":62283833,"identity":"f8a8852a-60af-4fe8-a297-dcb1b0e78955","added_by":"auto","created_at":"2024-08-12 13:04:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69378,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of local bivariate spatial autocorrelation between incidence and mortality rates due to COVID-19 and people who have adopted at least one protection measure against COVID-19, according to Brazilian Municipalities (2020-2021).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4698075/v1/6d59bdacf5d4b8644e74a3e0.jpg"},{"id":67252046,"identity":"54ece229-8e90-4fb5-88dd-425abe571956","added_by":"auto","created_at":"2024-10-23 03:24:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980313,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4698075/v1/19830aa7-46f1-4b3e-9bd4-456604e79311.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors associated with adherence or hesitation to protective measures that influenced the control of COVID-19 in Brazil in the pre-vaccine era","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSevere Acute Respiratory Syndrome caused by SARS-CoV-2 emerged at the end of 2019 in Wuhan from Hubei, China, and quickly spread around the world. COVID-19 was declared an International Public Health Emergency on January 30, 2020, and on March 11 of the same year it was declared a pandemic by the World Health Organization (WHO)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. On February 26, 2020, in the state of S\u0026atilde;o Paulo, Brazil registered the first case of the disease\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs June 3, 2022, COVID-19 has taken the lives of more than 6.2\u0026nbsp;million people worldwide\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In Brazil cases exceed the 30\u0026nbsp;million, where more than 660 thousand people died from the virus. These numbers could have been reduced if mass protection measures against COVID-19 were adopted\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the protection measures indicated by national and international organizations, non-pharmacological ones stand out, such as social distancing, hand hygiene, use of masks, cleaning and disinfection of environments, isolation of suspected and confirmed cases, and quarantine for cases of COVID-19\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePreventive behavior is one of the main strategies to contain the spread of the virus, especially at a time when vaccination is not yet adequately covered. Faced with a pandemic, caused by rapid viral spread among humans, it is important to understand the factors that influence people\u0026rsquo;s behavior in adherence or hesitation to protective measures and the way the population behaves during a health crisis. This understanding can help in the formulation of communication and intervention strategies aimed at minimizing the impact and dissemination of the disease.\u003c/p\u003e \u003cp\u003eScientific evidence reinforces the importance of adherence to protective measures in combating COVID-19\u003csup\u003e6\u003c/sup\u003e, however in Brazil there are still few studies with this objective, notably to highlight the factors associated with the risk behavior of the population about contracting and disseminating COVID-19. Given the above, the aim of the study was to analyze the behavior of the Brazilian population, adherence to protective measures that contributed to the lack of control and dissemination of the disease, a period in which the vaccine coverage was still incipient.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThis is a cross-sectional study, of the Survey type, conducted online between August 2020 and February 2021. The study was conducted according to the recommendations of the \u003cem\u003eStrengthening the Reporting of Observational Studies in Epidemiology''\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor study population was considered the general Brazilian population, who declared themselves resident in Brazil, aged 18 years or older, with access to the internet and who was willing to participate in the study. People who did not fully respond to the research instrument were excluded.\u003c/p\u003e \u003cp\u003eFor sample design, the study was based on convenient sample\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, using the snowball technique, which is characterized by not adopting margin of error calculations, since it is a non-probabilistic method. For data collection, the survey was \"\u003cem\u003eCOVID-19 Social Thermometer: Social Opinion\u003c/em\u003e\", which was developed and validated by researchers from the National School of Public Health of the New University of Lisbon (ENSP/UNL) from Portugal\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The adaptation of the survey to Brazil proved to be sufficiently valid and reliable for its wide application in the Brazilian population.\u003c/p\u003e \u003cp\u003eSurvey is composed of 151 fields, from multiple choice questions, in Checklist format, using Likert scale, with five possibilities for answers (totally agree, partially agree, partially disagree, totally disagree, I don\u0026acute;t know).\u003c/p\u003e \u003cp\u003eThe survey was developed and hosted on the Redcap platform of the University of S\u0026atilde;o Paulo (USP) Ribeir\u0026atilde;o Preto campus. Redcap is a \u003cem\u003esoftware\u003c/em\u003e of electronic data capture (\u003cem\u003eElectronic Data Capture\u003c/em\u003e \u0026ndash; EDC) browser-based and metadata-oriented with workflow methodology for designing clinical and observational research databases\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe survey was available to the eligible public through the websites of the research institutions participating in the study and through emails, \u0026ldquo;WhatsApp\u0026rdquo;, social networks, media and blogs. When accessing the survey, the Term of Consent was made available (TCLE) to the study participants, with the instructions for completing and presenting the purpose of the research.\u003c/p\u003e \u003cp\u003eFrom the set of variables of the questionnaire, it was considered as an outcome of interest the adoption of protection measures against COVID-19, which was evaluated by the following question: \u0026ldquo;Which Measures You Have Taken to Avoid Becoming Infected with COVID-19?\u0026rdquo; This question was evaluated continuously and included 13 answer options.\u003c/p\u003e \u003cp\u003eThe independent variables were: Age (18 to 39, 40 to 59, 60 or more), Gender (Male, Female), Schooling (Incomplete or less higher educations, Complete higher education, Postgraduate or more), Race/Color (White, Black, Brown, Yellow/Indigenous), Marital status (Married/Stable union, Single/Divorced/Discharged/Legally separated, Widowed), Have health insurance (No, Yes), Use of the Public Health System (No, Yes), Receiving a visit from the Community Health Agent (No, Yes), Receiving some government social support (No, Yes), Loss of monetary income during the pandemic (No, Yes), Smoking habit (No, Yes), Religion (some religion/ no religion), Present some chronical disease: Asthma (No, Yes), Hypertension (No, Yes), Diabetes Mellitus (No, Yes), Obesity (No, Yes).\u003c/p\u003e \u003cp\u003eFor the study descriptive and inferential analyses were performed. The descriptive occurred through the calculation of frequencies with 95% confidence intervals (95% CI). The descriptive analysis was performed considering the two research outcomes (did not adopt any measures, adopted all measures).\u003c/p\u003e \u003cp\u003eThe associations were evaluated by Poisson regression\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and considering the cross-sectional design of the study, the measure of association was the prevalence ratio (PR), with their respective 95% CI. Crude and adjusted analyzes were performed for the variables sex (male, female), skin color (white, black, brown or yellow/indigenous), age (18 to 39 years, 40 to 59, 60 years or older), schooling (incomplete higher education or less, complete higher education, postgraduate or more) and marital status (married, separated/unmarried, widowed). The analyses were performed using Stata software, version 15.1.\u003c/p\u003e \u003cp\u003eFor the spatial analysis, all 5,568 Brazilian municipalities\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e were considered as the unit of analysis, for which the incidence and mortality rates due to COVID-19 were calculated, with the number of cases (or deaths) in the numerator, the population of the municipality as denominator and the multiplication factor per 1,000 inhabitants.\u003c/p\u003e \u003cp\u003eThe Local Bivariate Moran Index\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e indicates the degree of association (positive or negative) between the value of the variable of interest in each region and another variable in the same region, and thus it is possible to map the statistically significant values, generating a choropletic map according to its classification.\u003c/p\u003e \u003cp\u003eIn this study, spatial autocorrelation between COVID-19 incidence and mortality rates was tested with people who adopted at least one measure of protection against COVID-19.\u003c/p\u003e \u003cp\u003eThe classification can be: \u003cb\u003eHigh-high\u003c/b\u003e (high values of incidence or mortality from COVID-19 with a high number of people who have adopted at least one protection measure against COVID-19), \u003cb\u003eLow-low\u003c/b\u003e (low values of incidence or mortality from COVID-19 with low number of people who have adopted at least one protection measure against COVID-19), \u003cb\u003eLow-high\u003c/b\u003e (low values of incidence or mortality from COVID-19 with a high number of people who have adopted at least one measure of protection against COVID-19) e \u003cb\u003eHigh-low\u003c/b\u003e (high COVID-19 incidence or mortality values with low number of people who have adopted at least one protection measure against COVID-19).\u003c/p\u003e \u003cp\u003eIt is noteworthy that the high and low values are classified according to the mean values of the variables of the neighboring regions\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 1,516 participants from the five macro-regions of Brazil. Table 1 shows the main characteristics of these participants, general and stratified by adoption of protection measures against COVID-19.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eDescription of the sample according to the adoption of protective measures against COVID-19, Brazil, 2020 - 2021 (n = 1516)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency and IC95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDid not take any measure\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency e 95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdoption all measures Frequency e 95%\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e73.0\u003c/p\u003e\n \u003cp\u003e70.7-75.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e15.8\u003c/p\u003e\n \u003cp\u003e13.7-18.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e84.2\u003c/p\u003e\n \u003cp\u003e81.9-86.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003cp\u003e24.8-29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e15.9\u003c/p\u003e\n \u003cp\u003e12.6-19.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e84.1\u003c/p\u003e\n \u003cp\u003e80.1-87.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 18 - 39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003cp\u003e32.1-37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003cp\u003e12.6-19.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e84.4\u003c/p\u003e\n \u003cp\u003e80.9-87.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 40 - 59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e41.8\u003c/p\u003e\n \u003cp\u003e39.2-44.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003cp\u003e9.8-15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e87.8\u003c/p\u003e\n \u003cp\u003e84.9-90.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; 60 or years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e23.6\u003c/p\u003e\n \u003cp\u003e21.5-25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003cp\u003e17.8-26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e70.1\u003c/p\u003e\n \u003cp\u003e73.3-82.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Incomplete higher or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003cp\u003e22.2-26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e20.2\u003c/p\u003e\n \u003cp\u003e16.3-24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e79.8\u003c/p\u003e\n \u003cp\u003e75.3-83.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Graduated\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003cp\u003e23.0-27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e18.7\u003c/p\u003e\n \u003cp\u003e15.0-23.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e81.3\u003c/p\u003e\n \u003cp\u003e77.0-85.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Post graduate or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003cp\u003e47.8-53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003cp\u003e9.4-14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e88.5\u003c/p\u003e\n \u003cp\u003e85.9-90.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkin color\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e68.1\u003c/p\u003e\n \u003cp\u003e65.6-70.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e15.5\u003c/p\u003e\n \u003cp\u003e13.4-17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e84.5\u003c/p\u003e\n \u003cp\u003e82.1-86.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003cp\u003e6.3-9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003cp\u003e16.9-33.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e75.9\u003c/p\u003e\n \u003cp\u003e67.0-83.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Brown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e22.2\u003c/p\u003e\n \u003cp\u003e20.2-24.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003cp\u003e10.2-17.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e86.5\u003c/p\u003e\n \u003cp\u003e82.3-89.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Yellow/Indigenous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003cp\u003e1.5-3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003cp\u003e9.3-38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e80.0\u003c/p\u003e\n \u003cp\u003e62.0-90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Married/Stable Union\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003cp\u003e44.5-49.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e14.8\u003c/p\u003e\n \u003cp\u003e12.3-17.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e85.2\u003c/p\u003e\n \u003cp\u003e82.4-87.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003eSeparated/Single\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e50.4\u003c/p\u003e\n \u003cp\u003e47.9-53.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003cp\u003e14.0-19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e83.5\u003c/p\u003e\n \u003cp\u003e80.6-86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003cp\u003e1.8-3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003cp\u003e9.6-35.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e80.6\u003c/p\u003e\n \u003cp\u003e64.5-90.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e26.9\u003c/p\u003e\n \u003cp\u003e24.7-29.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e18.0\u003c/p\u003e\n \u003cp\u003e14.5-22.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e82.0\u003c/p\u003e\n \u003cp\u003e77.8-85.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e73.1\u003c/p\u003e\n \u003cp\u003e70.8-75.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003cp\u003e12.2-16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e85.8\u003c/p\u003e\n \u003cp\u003e83.5-87.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of SUS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003cp\u003e33.6-38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e16.9\u003c/p\u003e\n \u003cp\u003e13.9-20.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e83.1\u003c/p\u003e\n \u003cp\u003e79.6-86.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.62190812720848%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.78798586572438%\"\u003e\n \u003cp\u003e64.0\u003c/p\u003e\n \u003cp\u003e61.4-66.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e14.4\u003c/p\u003e\n \u003cp\u003e12.3-16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.795053003533567%\"\u003e\n \u003cp\u003e85.6\u003c/p\u003e\n \u003cp\u003e83.2-87.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMost participants were female (73.0%), reported white skin color (68.1%), aged between 40 and 59 years (41.8%), single (as), divorced (as), discharged (as) or separated (as) judicially (50.4%) and had postgraduate level or more (50.4%). About 73.1% had health insurance and 64.0% used the Health Public System (SUS). It was observed that 19.1% (95%CI: 17.2 - 21.2) of the people did not adopt any protection measure against COVID-19.\u003c/p\u003e\n\u003cp\u003eFigure 1 shows the application of the Local Bivariate Moran Index, which refers to the incidence rate for COVID-19 with people who have adopted at least one protection measure against COVID-19 (Fig 1 - A), there is a positive spatial association (High-high) in municipalities of all big regions of Brazil, except for the Northeast region, and negative spatial association (Low-low) in all five Brazilian big regions.\u003c/p\u003e\n\u003cp\u003eRegarding the COVID-19 mortality rate with people who have adopted at least one protection measure against COVID-19 (Fig 1 \u0026ndash; B), it was possible to observe the same pattern described earlier, with municipalities classified as \u003cstrong\u003eHigh-high\u003c/strong\u003e (positive spatial association) present in all big regions of Brazil, with the exception of the Northeast, and classified as \u003cstrong\u003eLow-low\u003c/strong\u003e (negative spatial association) in all five Regions of the country.\u003c/p\u003e\n\u003cp\u003eRegarding the association between protective measures and sociodemographic factors, women took greater care in preventing COVID-19, and adopted protective measures 10% (95%CI: 1.05-1.15) more than men, results that remained significant even after adjustments for confounding factors (PR = 1.09; 95%CI: 1.04-1.14). In a previous studies developed in the United States, being female was considered a protective factor during the COVID-19 pandemic, since the female population has a greater adherence to the use of face masks when compared to men\u003csup\u003e16,17\u003c/sup\u003e. Historically, evidence shows that women tend to be more aware of their health status as well as seek care more proactively than men \u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn the analyzes performed in this study, the age group between 40 and 59 years was the one that had the highest adherence to protection measures against COVID-19. Other studies corroborate this finding, since it has been observed that the increase in age is associated with higher morbidity and mortality, especially non-communicable chronic diseases, so that with advancing age, people are more likely to adhere to disease prevention and protection measures\u003csup\u003e16\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA study conducted in Hong Kong during the swine flu pandemic showed that older people tend to take greater precautions with their health. Already during the COVID-19 pandemic in the United States, an observational study showed that the older the age the better adherence to protective measures\u003csup\u003e16,17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe results show that, even after adjusting for confounding factors, schooling was a protective factor against COVID-19. Those with complete higher education had a prevalence ratio of 8% (95%CI: 1.02-1.15) higher and those with postgraduate education or more 17% (95%CI: 1.11-1.24) had to adopt protective measures compared to those who had incomplete or less superior.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudies indicate that the level of education is an important factor for adherence to individual and collective protection measures since a lower level of education reflects less access to information\u003csup\u003e19\u003c/sup\u003e.\u0026nbsp;In Saudi Arabia, the level of knowledge about COVID-19 was directly associated with school level and family income\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eLower education is a social vulnerability, and the most vulnerable population generally has less access to information for decision-making and less financial conditions to remain in quarantine. Thus, it can be assumed that less favored communities, with lower education, aggravated by lower income and less access to health services, suffer more from health inequities that were even more evident during the pandemic.\u003c/p\u003e\n\u003cp\u003eThe results indicate that people self-declared black adopted fewer protective measures when compared to people with other skin color. Although the statistical significance of the categories is not maintained after adjusting for confounding factors, it is important to point out that in Brazil there are significant socioeconomic inequalities related to ethnic-racial issues, and most Brazilians with low income, lower education and less access to health services are black\u003csup\u003e21\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Brazil, 73% of the poor population is black\u003csup\u003e22\u003c/sup\u003e, it is worth noting that the average of deaths from COVID-19 in the five regions of Brazil was higher among black people, a fact that shows that this population is more exposed to being victims of the disease\u003csup\u003e21\u003c/sup\u003e.\u0026nbsp;Then it is important to reflect that inequality is of great importance in social determinants in health and that this will reflect on how this population adheres or hesitates to protective measures\u003csup\u003e19,21\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn a meta-analysis carried out during the COVID-19 pandemic, it was found that smokers are in the risk group of those most susceptible to complications of the disease, especially those who need hospitalization\u003csup\u003e23\u003c/sup\u003e and this fact was widely publicized in the media, causing greater concern in this group. In the present study, it was identified that people who self-declared as smokers showed more care regarding protection against the infection of the new coronavirus when compared to people who do not have the habit of smoking.\u003c/p\u003e\n\u003cp\u003eIn general, the arrival of the new coronavirus in the world has also shaken global religion, because it is known that historically religion and illness have a strong relation of mutual influence. In Brazil, the conflict between \u0026quot;science and religion\u0026quot; gained notoriety, causing political and social repercussions\u003csup\u003e24\u003c/sup\u003e. While the world was discussing the closure of mosques, suspension of religious meetings, cults and masses, in Brazil, the Presidential Decree n\u0026ordm; 10.292, of March 25, 2020, was published\u003csup\u003e25\u003c/sup\u003e, establishing that religious activities of all kinds should be regarded as essential services, thus exempt from measures of social isolation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe findings of this research showed that people with some religion adopted fewer protective measures when compared to people who defined themselves without religion, even after adjusting the confounding factors (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Association between adoption of protective measures and sociodemographic factors, Brazil, 2020 \u0026ndash; 2021\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGross results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eadjusted results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003cp\u003e1.05-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003cp\u003e1.04-1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;18 - 39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;40 - 59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003cp\u003e1.05-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003cp\u003e1.01-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;60 years or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e0.98-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e0.94-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Incomplete higher or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Graduated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003cp\u003e1.05-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e1.02-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Post graduate or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003cp\u003e1.16-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003cp\u003e1.11-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkin color\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003cp\u003e0.80-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e0.90-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Brown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e0.94-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003cp\u003e0.96-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eYellow/Indigenous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003cp\u003e0.82-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e0.83-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eMarried/Stable Union\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eSeparated/Single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003cp\u003e0.91-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e0.94-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e0.86-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e0.79-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003esmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003cp\u003e1.08-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003cp\u003e1.09-1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003cp\u003e1.03-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003cp\u003e1.03-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Adjusted for sex, skin color, age, education and marital status\u003c/p\u003e\n\u003cp\u003eTable 3 shows the association between the adoption of protective measures with situations of vulnerability and health services. The results showed that there was significance between the loss of income during the pandemic and adherence to protective measures, but the results lost statistical significance after adjustments to confounding factors. Similar results were found among those receiving government social support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. Association between adoption of protection measures with situations of vulnerability and health services, Brazil, 2020 - 2021\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGross results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eadjusted results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLoss of income during the pandemic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003cp\u003e0.92-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003cp\u003e0.95-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003egovernment aid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003cp\u003e0.81-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003cp\u003e0.89-1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCommunity health agent visit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e0.86-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003cp\u003e0.87-0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth plan\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003cp\u003e1.10-1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003cp\u003e1.02-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of SUS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.96-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e0.98-1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Adjusted for sex, skin color, age, education and marital status\u003c/p\u003e\n\u003cp\u003eParticipants who received visits from community health agents adopted fewer protective measures, even after adjusting for confounding factors (PR: 0.93; 95% CI: 0.93-0.98). Compared to those without health insurance, those who had health insurance were more likely to adhere to protective measures against COVID-19, even after adjusting for confounding factors (PR: 1.07; 95%CI: 1.02-1.13). The use of SUS showed no association with the adoption of protective measures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom a social perspective, it is possible to assume that those who have health insurance have better financial conditions and that those who receive visits from the community agents have a more unfavorable socioeconomic situation, so that adherence to social isolation, for example, would cause loss of source of income, since in Brazil, an important portion of the population works informally. This fact corroborates the findings about the lower income English population, who would like to be in isolation during the pandemic, but has this possibility decreased by up to three times in relation to the higher income segments\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTherefore, we emphasize the importance of income transfer policies for the portion of the population that cannot isolate themselves, as a way to expand the strategy to combat the pandemic, while minimizing the impact on social well-being.\u003c/p\u003e\n\u003cp\u003eTable 4 shows the association between adherence to protective measures and carrying non-communicable chronic diseases. Being a carrier of Asthma, Diabetes Melittus, Systemic Arterial Hypertension and Obesity were factors that increased the adherence of protective measures in the fight against COVID-19, even after adjustments to confounding factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. Association between adoption of protective measures with chronic diseases, Brazil, 2020 - 2021\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGross results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence ratio and 95% CI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eadjusted results\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsthma\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003cp\u003e1.17-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003cp\u003e1.10-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003cp\u003e1.25-1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003cp\u003e1.20-1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003cp\u003e1.27-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e1.23-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eObesity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp;No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003cp\u003e1.24-1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003cp\u003e1.17-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u003cstrong\u003eother diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.38977072310406%\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.5679012345679%\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003cp\u003e1.15-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.04232804232804%\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003cp\u003e1.08-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Adjusted for sex, skin color, age, education and marital status\u003c/p\u003e\n\u003cp\u003eAlthough the epidemiological profile of people affected by COVID-19 is not fully understood, studies indicate that the most severe forms of infection are more likely to occur in the elderly and in individuals with comorbidities\u003csup\u003e23\u003c/sup\u003e. In addition, mortality is also significantly higher among the elderly with pre-existing health conditions, such as systemic arterial hypertension, cardiovascular diseases and diabetes mellitus \u003csup\u003e27\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSeveral studies have reported that patients with chronic diseases have more unfavorable outcomes regarding hospitalizations and mortality\u003csup\u003e23\u003c/sup\u003e, and data from information systems in the country confirm this evidence. In the study \u0026quot;Social Barometer in Portugal\u0026quot;, the elderly and those with chronic diseases considered themselves at high risk of developing a severe course of the disease in case of COVID-19 infection\u003csup\u003e9\u003c/sup\u003e. This self-perception of risk is considered a protective factor, since those who consider themselves more likely to have complications from the disease tend to protect themselves more.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Brazil, these diseases affect almost half of people aged 65 years or older (44.6%), population vulnerable to COVID-19, namely due to age-related fragility and immune system decline.\u0026nbsp;In fact, morbidity seems to be the strongest determinant of the perception of risk of becoming ill and presenting complications resulting from the disease, which consequently increases adherence to protective measures.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The plausible risk of worsening COVID-19 has been widely reported by the media, medical societies, public health institutes, health authorities and patient organizations. Therefore, it is not surprising that people with comorbidities were particularly concerned about the risk of developing severe outcomes after COVID-19.\u003c/p\u003e\n\u003cp\u003eThis study evaluated the adherence of measures to protect the Brazilian population during the COVID-19 pandemic in the country. Data were collected at the first moment of the pandemic, where isolation measures were more restrictive, vaccination was restricted to priority groups (health professionals and the elderly), and much misinformation circulated. The results show that almost one fifth of the sample did not adopt any measures to protect themselves from the new coronavirus, and that sociodemographic determinants and the presence of chronic diseases are associated with preventive behaviors.\u003c/p\u003e\n\u003cp\u003eOther pandemics have occurred in history, some with repeated cycles for centuries, such as smallpox and measles, or for decades, such as cholera. Influenza pandemics by H1N1, H2N2, H3N3 and H5N1, known respectively as \u0026quot;Spanish flu\u0026quot;, \u0026quot;Asian flu\u0026quot;, \u0026quot;Hong Kong flu\u0026quot; and \u0026quot;avian flu\u0026quot;, however, the COVID-19 numbers are alarming.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn just over two years of the new coronavirus pandemic, there are already more than 530 million confirmed cases in the world, especially Brazil, which is in 3rd place in the ranking of cases, surpassing the range of 31 million infected people, lagging only the United States and India\u003csup\u003e3\u003c/sup\u003e. Such numbers may be associated with the low adherence of the population to protection measures against COVID-19, which may have been triggered by the little government investment in health education actions, as well as, by economic pressures against the measures of isolation and social distancing\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eUnderstanding how the population protects itself and what factors are considered protective is part of the process for formulating strategies to contain the virus. Being female, aged 40 to 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19.\u003c/p\u003e\n\u003cp\u003eAlthough the present study sought to obtain a representative sample of the Brazilian population, the method used, as a convenience sample in the online modality, represented a limitation of the study.\u0026nbsp;When it comes to online research, individuals with higher education are the most involved, a fact that can be observed in research with this characteristic approach observed in this study\u003csup\u003e28,29\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The difficulty of access to the internet, as well as the restricted access to some social layers has already been cited in the literature as a research bias, since the possibility that the participants of the research were composed mainly of people with high level of education and higher income, as already demonstrated in other studies\u003csup\u003e30\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEven in the face of the social vulnerability that the pandemic has generated in the country, a key point for its confrontation is the adhesion of protective measures. The survey data showed that most respondents are contributing to this purpose. This refers to the urgency of social protection measures and financial support, primarily for the most vulnerable social segments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt is suggested in future studies, the continuity of this with isonomy of the sample contemplating the greatest social diversity, since the method used excluded an important portion of the population that did not have access to the online survey. Certainly, a methodological design that includes follow-up or longitudinal measures is important for monitoring the behavior of all segments of the population and at all stages of the pandemic.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003e\u0026nbsp;Ethics approval and consent to participate.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Research Ethics Committee of the School of Nursing of Ribeir\u0026atilde;o Preto at the University of S\u0026atilde;o Paulo, under protocol number CAAE: 57933622.4.1001.5393.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed Consent\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInformed Consent was obtained from all the participants involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;Consent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll the material is owned by the authors and/or no permissions are required. The authors agree and consent that if the manuscript is accepted for publication, all copyright is transferred to the journal.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and material\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;I declare that the authors have no competing interests as defined by Discover Social Science and Health, or other interests that might be perceived to influence the results and/or discussion reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was sponsored by the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior\u0026mdash;Brasil (CAPES)\u0026mdash;Finance Code 001 Process: 88887.657730/2021-00 - Programa Impactos CAPES and by S\u0026atilde;o Paulo State Research Support Foundation (FAPESP) grant number 2021/08263-7. Post-doctoral fellowship (FAPESP process - 2022/03964-0); CNPQ (Research Productivity Scholarship - Process Processo: 307014/2022-3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eI declare that the authors Ara\u0026uacute;jo, JST participated in the design and writing of the manuscript. Delpino,FM participated in the statistical analysis of the study, Nascimento, CM participated as the second reviewer of the article and writing of the manuscript. Moura,HSD; Ramos, ACV; Berra TZ; Soares,DA participated in the revision of the studies. Arc\u0026ecirc;ncio RA, participated in the writing and revision of the final version of the articleAll authors reviewed and approved the final version to be published, assuming responsibility for all aspects of the work, including ensuring its accuracy and integrity.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eI declare that all data used can be accessed\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOPAS. \u003cem\u003eOMS declares public health emergency of international importance by outbreak of new coronavirus\u003c/em\u003e - OPAS/OMS | Organiza\u0026ccedil;\u0026atilde;o Pan-Americana da Sa\u0026uacute;de. Organiza\u0026ccedil;\u0026atilde;o Pan-Americana de Sa\u0026uacute;de https://www.paho.org/pt/news/30-1-2020-who-declares-public-health-emergency-novel-coronavirus (2020).\u003c/li\u003e\n\u003cli\u003ehttps://www.unasus.gov.br/noticia/coronavirus-brasil-confirma-primeiro-caso-da-doenca.\u003c/li\u003e\n\u003cli\u003eWORLD HEALTH ORGANIZATION (WHO). Coronavirus disease (COVID-19) Dashboard. Geneva: WHO; 2020b. Dispon\u0026iacute;vel em: https://covid19.who.int/. Accessed: 2021 July 2.\u003c/li\u003e\n\u003cli\u003eCENTERS FOR DISEASE CONTROL AND PREVENTION (CDC). 2022 Novel coronavirus, Wuhan, China. 2022. Available: https://www.cdc.gov/coronavirus/2022-nCoV/ summary.html. Accessed: 2022 July 3.\u003c/li\u003e\n\u003cli\u003eBrasil. Minist\u0026eacute;rio da Sa\u0026uacute;de. Secretaria de Vigil\u0026acirc;ncia em Sa\u0026uacute;de. 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London: Chapman and Hall/CRC.\u003c/li\u003e\n\u003cli\u003eInstituto Brasileiro de Geografia e Estat\u0026iacute;stica (IBGE). Brasil em s\u0026iacute;ntese [Internet]. 2022. Access: July 26, 2022. Available from: https://brasilemsintese.ibge.gov.br/\u003c/li\u003e\n\u003cli\u003eWagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther, 27(4):299-309, \u003cstrong\u003e2002\u003c/strong\u003e. \u003c/li\u003e\n\u003cli\u003e\u0026Aacute;vila, F. M. V. P., Nogueira, W. P., G\u0026oacute;es, F. G. B., Botelho, E. P., Gir, E., \u0026amp; Silva, A. C. de O. e. (\u003cstrong\u003e2021\u003c/strong\u003e). Medidas n\u0026atilde;o farmacol\u0026oacute;gicas para preven\u0026ccedil;\u0026atilde;o da covid-19 entre a popula\u0026ccedil;\u0026atilde;o idosa brasileira e fatores associados. Estudos Interdisciplinares Sobre O Envelhecimento, 26(2). https://doi.org/10.22456/2316-2171.110117\u003c/li\u003e\n\u003cli\u003eHaischer, M. H., Beilfuss, R., Hart, M. R., Opielinski, L., Wrucke, D., Zirgaitis, G. \u0026amp; Hunter, S. K. (\u003cstrong\u003e2020\u003c/strong\u003e). Who is wearing a mask? Gender-, age-, and location-related differences during the COVID-19 pandemic. Plos one, 15(10) doi: 10.1371/journal.pone.0240785.\u003c/li\u003e\n\u003cli\u003eHearne, B. N., \u0026amp; Ni\u0026ntilde;o, M. D. (\u003cstrong\u003e2021\u003c/strong\u003e). Understanding how race, ethnicity, and gender shape mask-wearing adherence during the COVID-19 pandemic: evidence from the COVID impact survey. J Racial Ethn Health Disparities, 1-8. doi: 10.1007/s40615-020-00941-1\u003c/li\u003e\n\u003cli\u003eOliveira, B. L. C. A. de, Thomaz, E. B. A. F. e S, Raimundo A. The association between skin color/race and health indicators in elderly Brazilians: a study based on the Brazilian National Household Sample Survey (\u003cstrong\u003e2008\u003c/strong\u003e). Cadernos de Sa\u0026uacute;de P\u0026uacute;blica [online]. 2014, v. 30, n. 7 [Acesseced August 11, 2022] , pp. 1438-1452. Available: \u0026lt;https://doi.org/10.1590/0102-311X00071413\u0026gt;. ISSN 1678-4464. https://doi.org/10.1590/0102-311X00071413.\u003c/li\u003e\n\u003cli\u003eAlahdal, H., Basingab, F., Alotaibi, R. An analytical study on the awareness, attitude and practice during the COVID-19 pandemic in Riyadh, Saudi Arabia. J Infect Public Health. \u003cstrong\u003e2020\u003c/strong\u003e Oct;13(10):1446-1452. doi: 10.1016/j.jiph.2020.06.015. Epub 2020 Jun 17. PMID: 32563674; PMCID: PMC7832465.\u003c/li\u003e\n\u003cli\u003e\u003cem\u003e. \u003c/em\u003e\u003cem\u003eSthel, F.G., Silva, L.S.\u003c/em\u003eA crise da pandemia da COVID-19 desnuda o racismo estrutural no Brasil. Revista da Associa\u0026ccedil;\u0026atilde;o Portuguesa Portuguesa de Sociologia.2021 DOI: https://doi.org/10.30553/sociologiaonline.2021.26.1\u003c/li\u003e\n\u003cli\u003eInstituto Brasileiro de Geografia e Estat\u0026iacute;stica (IBGE). 2020 [Internet]. Censo demogr\u0026aacute;fico. [Accessed 2020 May 22]. Available: https://cidades.ibge.gov.br/brasil\u003c/li\u003e\n\u003cli\u003eEmami, A., Javanmardi, F., Pirbonyeh, N., Akbari, A. Prevalence of Underlying Diseases in Hospitalized Patients with COVID-19: a Systematic Review and Meta-Analysis. Arch Acad Emerg Med. \u003cstrong\u003e2020\u003c/strong\u003e Mar 24;8(1):e35. PMID: 32232218; PMCID: PMC7096724.\u003c/li\u003e\n\u003cli\u003eCarletti, A. Nobre, F. A Religi\u0026atilde;o Global no Contexto da Pandemia de Covid-19 e como implica\u0026ccedil;\u0026otilde;es pol\u0026iacute;tico-religiosas no Brasil. 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PMID: 33397669; PMCID: PMC7783373.\u003c/li\u003e\n\u003cli\u003e\u0026Eacute;tard, J-F., Vanhems, P., Atlani-Duault, L., Ecochard R. Potential lethal outbreak of coronavirus disease (COVID-19) among the elderly in nursing homes and long-term facilities, France, \u003cstrong\u003e2020 \u003c/strong\u003eMarch. , 2020;25(15):pii=2000448. https://doi.org/10.2807/1560-7917.ES.2020.25.15.2000448\u003c/li\u003e\n\u003cli\u003eSzwarcwald, C. L. et al\u003cem\u003e.\u003c/em\u003e ConVid - Behavior Survey by the Internet during the COVID-19 pandemic in Brazil: Conception and application methodology. Cad. Saude Publica 37, e00268320 (\u003cstrong\u003e2021\u003c/strong\u003e).\u003c/li\u003e\n\u003cli\u003eFaleiros, F. et al. Use of virtual questionnaire and dissemination as a data collection strategy in scientific studies. Texto \u0026amp; Contexto - Enfermagem [online]. \u003cstrong\u003e2016,\u003c/strong\u003e v. 25, n. 04 [Accessed August 11 2022], e3880014. Available: \u0026lt;https://doi.org/10.1590/0104-07072016003880014\u0026gt;. Epub 2016 Out 24 . ISSN 1980-265X. https://doi.org/10.1590/0104-07072016003880014\u003c/li\u003e\n\u003cli\u003eBaz\u0026aacute;n, P. R. et al. COVID-19 information exposure in digital media and implications for employees in the health care sector: findings from an online survey. Einstein Sao Paulo Braz\u003cem\u003e.\u003c/em\u003e 18, eAO6127 (\u003cstrong\u003e2020\u003c/strong\u003e).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Protection Measures, Observational Study, Pandemics","lastPublishedDoi":"10.21203/rs.3.rs-4698075/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4698075/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePreventive behavior is one of the main strategies to contain the spread of the coronavirus, understand the factors that influence adherence or hesitation to protective measures and the way the population behaves during a health crisis is of great importance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim:\u003c/strong\u003e To analyze the factors associated with adherence to protection measures against Covid-19 in Brazil.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod: \u003c/strong\u003ecross-sectional study, survey type online, between the period of August 2020 and February 2021. The population included in the study were Brazilians, aged 18 years or older. Non-probabilistic sampling was used to obtain the sample. The data was stored on the \"Redcap\" platform and analyzed in a descriptive and inferential approach.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The sample consisted of 1,516 people, women adopted 10% more protective measures than men, people with higher education level and higher income, within the age group between 40-59 years, were those who most adhered to the measures imposed by health agencies. Carrier of Asthma, Diabetes Mellitus, Systemic Arterial Hypertension, Obesity and smoking were factors that increased the adherence of protective measures in the fight against COVID-19.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Being female, aged between 40 and 59 years, higher education, smoking, not having a religion, having health insurance, and being a carrier of chronic diseases were associated with greater adherence to protective measures against COVID-19.\u003c/p\u003e","manuscriptTitle":"Factors associated with adherence or hesitation to protective measures that influenced the control of COVID-19 in Brazil in the pre-vaccine era","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-12 13:04:14","doi":"10.21203/rs.3.rs-4698075/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7f787782-bde5-4394-879c-5fd63def6e61","owner":[],"postedDate":"August 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-23T03:23:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-12 13:04:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4698075","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4698075","identity":"rs-4698075","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}