Prevalence and Predictors of Emotional Eating among Healthy Young Saudi Women during the COVID-19 Pandemic.
Sara Al-MusharafPublished in: Nutrients (2020)
Emotional eating (EE) is prevalent among women and is associated with obesity. The coronavirus 2019 (COVID-19) pandemic and mandatory quarantine increased the risk of mental symptoms and, inferentially, emotional eating (EE). We investigated the EE prevalence and predictors during this pandemic. Overall, 638 women, ages 18-39, completed an online survey incorporating the Emotional Eating Scale, Perceived Stress Scale, Generalized Anxiety Disorder-7 Scale, Patient Health Questionnaire-9, Pittsburgh Sleep Quality Index, and Global Physical Activity Questionnaire. We asked about nutrition and collected data on weight, height, and pandemic responses. Most respondents (47.2%) reported low EE; 40.4% were "moderate" and 12.4% "high" emotional eaters; 42.8% reported depression, 27% anxiety, 71% moderate stress, and 12.5% severe stress. The main EE indicators/predictors were fat intake (β = 0.192, p = 0.004), number of meals (β = 0.187, p < 0.001), sugar consumption (β = 0.150, p < 0.001), body mass index (β = 0.149, p < 0.001), stress (β = 0.143, p = 0.004), energy intake (β = 0.134, p = 0.04), and fast food intake frequency (β = 0.111, p < 0.01). EE score correlated negatively with increased family income (β = -0.081, p = 0.049). Higher stress correlated with worse sleep, less sleep, and less physical activity. Emotional eating is common among young Saudi women during the pandemic. We recommend healthy food choices and increased physical activity to improve sleep and mitigate stress.
Keyphrases
- physical activity
- sleep quality
- body mass index
- sars cov
- polycystic ovary syndrome
- weight loss
- weight gain
- coronavirus disease
- depressive symptoms
- stress induced
- healthcare
- type diabetes
- risk factors
- adipose tissue
- pregnancy outcomes
- cross sectional
- cervical cancer screening
- pregnant women
- big data
- social media
- risk assessment
- middle aged
- high intensity
- electronic health record
- saudi arabia
- mass spectrometry
- machine learning
- human health
- heat stress
- health information
- skeletal muscle