OBJECTIVE: The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters' perceptions and sentiments of healthy eating through text mining techniques.
METHODS: This paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.
RESULTS: With a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.
CONCLUSIONS: This study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.
Materials and Methods: The 500 individuals of both males and females aged 40 years and older with missing posterior teeth and not rehabilitated with any prosthesis were gone through a clinical history, intraoral examination, and anthropometric measurement to get information regarding age, sex, socioeconomic status, missing posterior teeth, and body mass index (BMI). Subjects were divided into five groups according to BMI (underweight > 18.5 kg/m2, normal weight 18.5-23 kg/m2, overweight 23-25 kg/m2, obese without surgery 25-32.5 kg/m2, obese with surgery < 32.5 kg/m2). Multivariate logistic regression was used to adjust data according to age, sex, number of missing posterior teeth, and socioeconomic status.
Results: People with a higher number of tooth loss were more obese. Females with high tooth loss were found to be more obese than male. Low socioeconomic group obese female had significantly higher tooth loss than any other group. No significant relation between age and obesity was found with regard to tooth loss.
Conclusion: The BMI and tooth loss are interrelated. Management of obesity and tooth loss can help to maintain the overall health status.
Methods: A total of 380 women who had used the same contraceptive method for at least twelve months were recruited in this study. Covariance analysis was done to compare the weight gain between hormonal and non-hormonal contraceptive users, while studying the same confounders [age, household income, number of pregnancies, and baseline body mass index (BMI)].
Results: Hormonal methods were more commonly used. The mean weight gain among hormonal users (adjusted mean 2.85, 95% CI 2.45, 3.24) was significantly higher than non-hormonal users (adjusted mean 0.46, 95% CI -0.73, 1.65; p-value <0.001), after controlling for age, household income, number of pregnancies, and baseline BMI.
Conclusion: The possibility of weight gain following the use of hormonal methods should be investigated and non-hormonal methods should be considered to prevent weight gain.