0387/2025 - DESVELANDO AS CONDIÇÕES DE ESTUDO REMOTO DURANTE A PANDEMIA DE COVID-19 E AS ASSOCIAÇÕES COM A (IN)SEGURANÇA ALIMENTAR UNVEILING REMOTE STUDY CONDITIONS DURING THE COVID-19 PANDEMIC AND THE ASSOCIATIONS WITH FOOD INSECURITY
Objetivou-se identificar o perfil das condições de estudo remoto emergencial (ERE), de (in)segurança alimentar e, as associações existentes, em uma população de 2.361 estudantes de instituições de ensino superior (IES) brasileiras, na primeira onda da COVID-19. Baseado em Mercuri (1992), utilizou-se fatores materiais (tecnológicos, conectividade, mobiliário), temporais (período do curso), espaciais (domicílio) e pessoais (horas de sono) para identificar o construto condições de estudo remoto (ER) utilizando a análise de classes latentes. Qui-quadrado de Pearson e regressão multinomial testaram as associações. Verificou-se população em sua maioria feminina, não casada, renda < R$3.000,00. A condição de insegurança alimentar (IA) foi identificada em 44,4% dos domicílios. O modelo com 4 classes caracterizou as condições de estudo em Vulnerável (CL1), Adequada (CL2), de Risco (CL3) e em Desequilíbrio (CL4), com maior proporção na CL1 (32,2%). A IA moderada/grave se associou com a CL1 e CL3, demonstrando que estudantes conviveram simultaneamente com a fome e condições inadequadas para estudar, durante a pandemia. Mitigar efeitos da COVID-19, principalmente entre os grupos mais afetados, é papel das políticas públicas, dentro e fora das IES.
Palavras-chave:
Estudantes, Instituições de ensino superior, Análise de classes latentes, Insegurança alimentar, Estudo remoto.
Abstract:
The objective was to identify the profile of emergency remote study (ERS) conditions, food (in)security and existing associations, in a population of 2,361 students from Brazilian Universities, in the first wave of COVID-19. Based on Mercuri (1992), material (technological, connectivity, furniture), temporal (course period), spatial (home) and personal (hours of sleep) factors were used to identify the construct remote study (RS) conditions using latent class analysis. Pearson chi-square and multinomial regression tested the associations. A population was found to be mostly female, unmarried, with income < R$3,000.00. Food insecurity was identified in 44.4% of households. The model with 4 classes characterized the ERS conditions as Vulnerable (LC1), Adequate (LC2), Risk (LC3) and Imbalanced (LC4), with a higher proportion in LC1 (32,2%). Moderate/severe food insecurity was associated with LC1 and LC3, demonstrating that students lived simultaneously with hunger and inadequate conditions to study during the pandemic. Mitigating the effects of COVID-19, especially among the most affected groups, is the role of public policies, inside and outside universities.
Keywords:
Students, Universities, Latent Class Analysis, Food Insecurity, Remote study.
UNVEILING REMOTE STUDY CONDITIONS DURING THE COVID-19 PANDEMIC AND THE ASSOCIATIONS WITH FOOD INSECURITY
Resumo (abstract):
The objective was to identify the profile of emergency remote study (ERS) conditions, food (in)security and existing associations, in a population of 2,361 students from Brazilian Universities, in the first wave of COVID-19. Based on Mercuri (1992), material (technological, connectivity, furniture), temporal (course period), spatial (home) and personal (hours of sleep) factors were used to identify the construct remote study (RS) conditions using latent class analysis. Pearson chi-square and multinomial regression tested the associations. A population was found to be mostly female, unmarried, with income < R$3,000.00. Food insecurity was identified in 44.4% of households. The model with 4 classes characterized the ERS conditions as Vulnerable (LC1), Adequate (LC2), Risk (LC3) and Imbalanced (LC4), with a higher proportion in LC1 (32,2%). Moderate/severe food insecurity was associated with LC1 and LC3, demonstrating that students lived simultaneously with hunger and inadequate conditions to study during the pandemic. Mitigating the effects of COVID-19, especially among the most affected groups, is the role of public policies, inside and outside universities.
Palavras-chave (keywords):
Students, Universities, Latent Class Analysis, Food Insecurity, Remote study.
Assunção, TS, Queiroz, VAO, Araújo, MPN, Cunha, CM, Santana, MLP, Barroso, RRF. DESVELANDO AS CONDIÇÕES DE ESTUDO REMOTO DURANTE A PANDEMIA DE COVID-19 E AS ASSOCIAÇÕES COM A (IN)SEGURANÇA ALIMENTAR. Cien Saude Colet [periódico na internet] (2025/nov). [Citado em 06/11/2026].
Está disponível em: http://cienciaesaudecoletiva.com.br/artigos/desvelando-as-condicoes-de-estudo-remoto-durante-a-pandemia-de-covid19-e-as-associacoes-com-a-inseguranca-alimentar/19863
