Physical Activity Is Related to Mood States, Anxiety State and Self-Rated Health in COVID-19 Lockdown

• Main Authors: Rafael E. Reigal, José A. Páez-Maldonado, José L. Pastrana-Brincones, Juan P. Morillo-Baro, Antonio Hernández-Mendo, Verónica Morales-Sánchez
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Sustainability
• Subjects: physical activity; moods; self-rated health; state anxiety; COVID-19
• Online Access: https://www.mdpi.com/2071-1050/13/10/5444

The main goal of this research is to study the relationships between physical activity, mood states and self-rated health in the Spanish lockdown (March 2020–April 2020) due to the state of alarm caused by COVID-19. The participants were 328 people aged between 19 and 59 years (M = 37.06; SD = 10.82). Females comprised 63.70% of the participants, and 36.30% were male. An associative, comparative and predictive design was used in this research. The International Physical Activity Questionnaire (IPAQ), the Profile of Mood State (POMS), the state anxiety scale of the State-Trait Anxiety Questionnaire (STAI) and the General Health Questionnaire GHQ−12 were applied in order to measure the study variables. Both correlation and linear regression analyses were performed, showing that physical activity is positively related to health perception and mood. Similarly, data have shown that moderate physical practice predicts better health perceptions and positive mood states than vigorous physical activity. Specifically, moderate physical activity is the only variable that predicts the anxiety state (<i>R</i> = 0.22; <i>R</i>²<i>adjusted</i> = 0.05; <i>F</i> = 15.51; <i>p</i> < 0.001). In addition, it has been detected that mood is related to the perception of the state of health. Outcomes suggest that practicing moderate physical activity during these types of situations could amortize its negative effects on psychological health and benefit a more positive mental state. Future studies should consider the employment status of the sample to detect possible differences based on this variable.