RESUMO Objetivo O estudo teve como objetivo avaliar os fatores associados ao burnout entre estudantes universitários que estudaram online durante o bloqueio da COVID-19, com foco em hábitos nutricionais e de estilo de vida. Métodos Este estudo transversal baseado na web foi realizado com estudantes universitários em Türkiye. Características demográficas, comportamentos nutricionais, uso de suplementos nutricionais, escala Multidimensional COVID-19 e Maslach Burnout Inventory-Student Scale de estudantes universitários foram questionados por meio de um questionário online. Resultados Um total de 747 estudantes (faculdades de ciências da saúde: 68,9% e faculdades não relacionadas à saúde: 31,1%) participaram do estudo. Estudantes de áreas não relacionadas à saúde apresentaram maiores pontuações medianas em exaustão emocional, cinismo e pontuação total na escala Multi-Dimensional COVID-19 do que estudantes de ciências da saúde. A pontuação de exaustão emocional estava positivamente associada aos pensamentos sobre a COVID-19 (β=0,266, p<0,001) e negativamente associada à atenção à dieta (β=-1.142, p=0,005). Estudantes que consumiram carne, ovos e legumes pelo menos uma vez ao dia tiveram menores pontuações de exaustão emocional (β=-0,925, p=0,029) e cinismo (β= -0,804, p=0,025), e maior eficácia acadêmica (β=0,550, p=0,034). O consumo diário de leite e produtos lácteos foi negativamente relacionado à exaustão emocional (β=-0,844, p=0,033) e cinismo (β=-0,817, p=0,015). Estudantes que consumiram pelo menos cinco porções diárias de frutas e vegetais tiveram uma maior eficácia acadêmica (β=0,669, p=0,015). Conclusão Faculdade, série, pensamentos sobre a COVID-19, precauções relacionadas à COVID-19 e atenção à dieta são os fatores que afetam o burnout dos estudantes durante a pandemia da COVID-19. A educação em saúde e a adoção de hábitos alimentares saudáveis são benéficas para combater o burnout em períodos críticos, como pandemias. COVID19, COVID19 COVID 19, 19 vida Türkiye demográficas COVID-1 InventoryStudent Inventory Student 74 689 68 9 68,9 31,1% 311 31 1 MultiDimensional Multi Dimensional β=0,266, β0266 β 0 266 (β=0,266 p<0,001 p0001 p 001 β=1.142, β1142 β= 1.142, 142 (β=-1.142 p=0,005. p0005 p=0,005 . 005 p=0,005) carne β=0,925, β0925 0,925, 925 (β=-0,925 p=0,029 p0029 029 (β 0,804, 0804 804 -0,804 p=0,025, p0025 p=0,025 , 025 p=0,025) β=0,550, β0550 550 (β=0,550 p=0,034. p0034 p=0,034 034 p=0,034) β=0,844, β0844 0,844, 844 (β=-0,844 p=0,033 p0033 033 β=0,817, β0817 0,817, 817 (β=-0,817 p=0,015. p0015 p=0,015 015 p=0,015) β=0,669, β0669 669 (β=0,669 Faculdade série COVID19. 19. críticos pandemias COVID1 COVID- 7 6 68, 31,1 3 β=0,266 β026 26 (β=0,26 p<0,00 p000 00 β=1.142 β114 1142 1.142 14 (β=-1.14 p=0,00 β=0,925 β092 0925 0,925 92 (β=-0,92 p=0,02 p002 02 0,804 080 80 -0,80 β=0,550 β055 55 (β=0,55 p003 p=0,03 03 β=0,844 β084 0844 0,844 84 (β=-0,84 β=0,817 β081 0817 0,817 81 (β=-0,81 p001 p=0,01 01 β=0,669 β066 66 (β=0,66 31, β=0,26 β02 2 (β=0,2 p<0,0 p00 β=1.14 β11 114 1.14 (β=-1.1 p=0,0 β=0,92 β09 092 0,92 (β=-0,9 0,80 08 8 -0,8 β=0,55 β05 5 (β=0,5 β=0,84 β08 084 0,84 (β=-0,8 β=0,81 081 0,81 β=0,66 β06 (β=0,6 β=0,2 β0 (β=0, p<0, p0 β=1.1 β1 11 1.1 (β=-1. p=0, β=0,9 09 0,9 (β=-0, 0,8 -0, β=0,5 β=0,8 β=0,6 β=0, (β=0 p<0 β=1. 1. (β=-1 p=0 0, (β=-0 -0 β=0 p< β=1 (β=- p= -
ABSTRACT Objective The study aimed to assess the factors associated with burnout among university students studying online during the COVID-19 lockdown, with a focus on nutrition and lifestyle habits. Methods This cross-sectional web-based study was conducted with university students in Türkiye. Demographic characteristics, dietary habits, dietary supplement usage, the Multidimensional COVID-19 scale, and the Maslach Burnout Inventory-Student Scale of university students were questioned with an online survey. Results: A total of 747 students (health science faculties:68.9% and non-health faculties:31.1%) participated in the study. Non-health sciences students had higher median scores of emotional exhaustion (17 vs 15), cynicism (13 vs 10), and total Multi-Dimensional COVID-19 scale (84 vs 80) than health sciences students (respectively; p=0.001, p<0.001, p<0.001). The emotional exhaustion score was positively associated with thoughts about COVID-19 (β=0.266, p<0.001) and negatively with paying attention to diet (β=-1,142, p=0.005). Students who consumed meat, eggs, and legumes at least once a day had lower emotional exhaustion (β=-0.925, p=0.029), cynicism scores (β=-0.804, p=0.025), and higher academic efficacy (β= 0.550, p=0.034). Consumption of milk and dairy products at least once a day was negatively related to emotional exhaustion (β=-0.844, p=0.033) and cynicism (β=-0.817, p=0.015). Students who consumed at least five daily portions of fruit and vegetables had greater academic efficacy (β=0.669, No-BreakpNo-Break=0.015). Conclusion Faculty, grade, thoughts about COVID-19, precautions taken related to COVID-19, and paying attention to diet are the factors that affect students’ burnout during the COVID-19 pandemic. Health education and adopting healthy eating habits are beneficial for combating burnout in critical periods such as pandemics. COVID19 COVID 19 COVID-1 lockdown crosssectional cross sectional webbased web based Türkiye characteristics usage InventoryStudent Inventory Student survey Results 74 faculties68.9% faculties689 faculties 68.9% 68 9 faculties:68.9 nonhealth non faculties31.1% faculties311 31.1% 31 1 faculties:31.1% Nonhealth Non 17 (1 15, 15 , 15) 13 10, 10 10) MultiDimensional Multi Dimensional 84 (8 80 respectively (respectively p0001 p 0 001 p=0.001 p<0.001 p<0.001. . β=0.266, β0266 β 266 (β=0.266 β=1,142, β1142 β= 1,142, 142 (β=-1,142 p=0.005. p0005 p=0.005 005 p=0.005) meat eggs β=0.925, β0925 0.925, 925 (β=-0.925 p=0.029, p0029 p=0.029 029 p=0.029) β=0.804, β0804 0.804, 804 (β=-0.804 p=0.025, p0025 p=0.025 025 p=0.025) (β 0550 550 0.550 p=0.034. p0034 p=0.034 034 p=0.034) β=0.844, β0844 0.844, 844 (β=-0.844 p=0.033 p0033 033 β=0.817, β0817 0.817, 817 (β=-0.817 p=0.015. p0015 p=0.015 015 p=0.015) β=0.669, β0669 669 (β=0.669 NoBreakpNoBreak=0.015. NoBreakpNoBreak0015 NoBreakpNoBreak No BreakpNo Break=0.015 Break No-BreakpNo-Break=0.015) Faculty grade COVID19, 19, pandemic pandemics COVID1 COVID- 7 faculties68 faculties68.9 689 68.9 6 faculties:68. faculties31 faculties31.1 311 31.1 3 faculties:31.1 ( 8 p000 00 p=0.00 p<0.00 β=0.266 β026 26 (β=0.26 β=1,142 β114 1142 1,142 14 (β=-1,14 β=0.925 β092 0925 0.925 92 (β=-0.92 p002 p=0.02 02 β=0.804 β080 0804 0.804 (β=-0.80 055 55 0.55 p003 p=0.03 03 β=0.844 β084 0844 0.844 (β=-0.84 β=0.817 β081 0817 0.817 81 (β=-0.81 p001 p=0.01 01 β=0.669 β066 66 (β=0.66 NoBreakpNoBreak=0.015 NoBreakpNoBreak001 Break0015 Break=0.01 No-BreakpNo-Break=0.015 faculties6 faculties68. 68. faculties:68 faculties3 faculties31. 31. faculties:31. p00 p=0.0 p<0.0 β=0.26 β02 2 (β=0.2 β=1,14 β11 114 1,14 (β=-1,1 β=0.92 β09 092 0.92 (β=-0.9 β=0.80 β08 080 0.80 (β=-0.8 05 5 0.5 β=0.84 084 0.84 β=0.81 081 0.81 β=0.66 β06 (β=0.6 NoBreakpNoBreak=0.01 NoBreakpNoBreak00 Break001 Break=0.0 No-BreakpNo-Break=0.01 faculties:6 faculties:31 p0 p=0. p<0. β=0.2 β0 (β=0. β=1,1 β1 11 1,1 (β=-1, β=0.9 09 0.9 (β=-0. β=0.8 08 0.8 0. β=0.6 NoBreakpNoBreak=0.0 NoBreakpNoBreak0 Break00 Break=0. No-BreakpNo-Break=0.0 faculties: faculties:3 p=0 p<0 β=0. (β=0 β=1, 1, (β=-1 (β=-0 NoBreakpNoBreak=0. Break0 Break=0 No-BreakpNo-Break=0. p= p< β=0 β=1 (β=- NoBreakpNoBreak=0 Break= No-BreakpNo-Break=0 NoBreakpNoBreak= No-BreakpNo-Break= No-BreakpNo-Break