Thai’s Health Behaviors and Their Associated Factors among Three Age Groups during COVID-19 Pandemic

Abstract

Background and Rationale: COVID-19 control measures impacted on stress, alcohol, and tobacco consumption, including physical inactivity and sedentary lifestyle among populations. As age is a factor in the health belief model that affected individual beliefs throughout life-course, this study aimed to explore health-related behaviors by age groups during the COVID-19 pandemic, compared to the pre-pandemic. Methodology: A cross-sectional study was done among 7,731 Thai people aged 15 years and older, through multistage sampling of the total 13 health regions and proportionate to population size of selected provinces by three age groups (adolescent: 15-24 years, working age group: 25-59 years, and elderly: 60 years and older). Face-to-face interview captured changes in health-related behaviors (increase, no change, and decrease) then analyzed by ordinal logistic regression. Results: During the COVID-19 pandemic 33.3% of Thai people were current drinker, 18.3% were current smoker, 73.5% had sedentary behavior, 6.8% were physical inactive, more than 70% had vegetable and fruit in some meal/day, 77.0% had sugar drink, and 57.7% ate fast-food. Compared to pre-pandemic, 3 out of 8 behaviors were going in positive direction - alcohol consumption (27.0%), sugar drink (11.1%), and fast-food eating (12.7%) - whereas tobacco consumption, sedentary life, physical activity, and eating vegetable and fruit were going in the opposite direction. Negative directions happened among age group 15-24 years the most, followed by the 60 years and older. Taking the 15-24 years as the reference group, the working age and the elderly had less sedentary and physical inactivity, the working age ate fast-food more frequently and the elderly even more than among adolescent group. Also, elderly group had higher risk of eating less vegetable and fruit compared to adolescent group. The 15-24 years had the most 4 highest negative health behavior changes compared to pre-pandemic including sedentary life, less physical activity, more sugar-drink (p < 0.01), and more fast-food. Conclusion: During the COVID-19 pandemic, the adolescent had most negative health-related behaviors, whereas the working age and the older persons had higher risk of having fast-food than the adolescent. Government should further develop interventions specific to age groups. New interventions should create enabling healthy environments to adolescent and the vulnerable groups during the pandemic.