Gender Differences in Health Behaviors and Association With Mental Wellbeing During the Initial Covid-19 Pandemic Lockdown in Arab Countries

Abstract

Background and Objective: The COVID-19 pandemic lockdown has been shown to be associated with poor lifestyle behaviors and poor mental wellbeing. It is suggested that females have shouldered most of the burden widening the gender inequity gap in the Arab region. The objective of this study is to examine differences between males and females with respect to their lifestyle behaviors (mainly physical activity, sleep and diet) and to explore gender differences in the association between those lifestyle behaviors and mental wellbeing.

Methods: This is a secondary data analyses of a cross-sectional study that recruited 2754 adults from 12 Arab countries via email and various social media platforms using snowball nondiscriminatory sampling. The questionnaire collected data on lifestyle factors using the following tools: Food Frequency Questionnaire (FFQ), International Physical Activity questionnaire (IPAQ), WHO-5 wellbeing score, and Pittsburgh Sleep Quality Index (PSQI). Binary logistic regression with gender as the main exploratory variable was run to estimate the association between gender and lifestyle factors, and further examine the association between lifestyle factors and mental wellbeing; separate models were run for males and females followed by interaction analysis to test if the gender differences are statistically significant.

Results: After controlling for sociodemographics, males had higher odds of being current smokers vs. non-smokers (p-value<0.0001) and higher odds of being moderately or intensely physically active (vs. not) (p-value<0.0001). Females had higher odds of having being in the above median dietary split (p-value<0.0001). Sleep did not vary by gender. Lifestyle factors that were associated with mental wellbeing include: smoking, sleep, physical activity and diet. The magnitude of the associations did not vary by gender, except for association between high (vs. low) level physical activity and mental wellbeing which was statistically significantly [p-value: 0.002] higher for males [OR: 9.07, 95%CI: (5.81; 14.16)] than females [OR: 4.15, 95%CI: (4.34; 6.33)].

Conclusion: Our study revealed that there are significant differences between males and females in lifestyle factors, with no significant gender differences in the association between mental wellbeing and lifestyle factors, except in high levels of physical activity. Healthy lifestyle factors were similarly associated with good mental wellbeing in males and females suggesting that future interventions could aim to improve lifestyle behaviors which would in turn aid in promoting good mental wellbeing in both genders.