DESIGN AND SETTINGS: This is a retrospective study of all patients who had undergone coronary angioplasty from 2007 to 2009 in 11 hospitals across Malaysia.
METHODS: Data were obtained from the NCVD-PCI Registry, 2007 to 2009. Patients were categorized into 2 groups-young and old, where young was defined as less than 45 years for men and less than 55 years for women and old was defined as more than or equals to 45 years for men and more than or equals to 55 years for women. Patients' baseline characteristics, risk factor profile, extent of coronary disease and outcome on dis.charge, and 30-day and 1-year follow-up were compared between the 2 groups.
RESULTS: We analyzed 10268 patients, and the prevalence of young CAD was 16% (1595 patients). There was a significantly low prevalence of Chinese patients compared to other major ethnic groups. Active smoking (30.2% vs 17.7%) and obesity (20.9% vs 17.3%) were the 2 risk factors more associated with young CAD. There is a preponderance toward single vessel disease in the young CAD group, and they had a favorable clinical outcome in terms of all-cause mortality at discharge (RR 0.49 [CI 0.26-0.94]) and 1-year follow-up (RR 0.47 [CI 0.19-1.15]).
CONCLUSION: We observed distinctive features of young CAD that would serve as a framework in the primary and secondary prevention of the early onset CAD.
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.
METHODS: The social media analytics site SocialBlade.com was used to identify the most popular YouTube videos (n = 250) targeting children. Ads encountered while viewing these videos were recorded and analyzed for type of product promoted and ad format (video vs. overlay). Food and beverage ads were further coded based on food category and persuasive marketing techniques used.
RESULTS: In total 187 ads were encountered in sampled videos. Food and beverage ads were the most common at 38% (n=71), among which 56.3% (n = 40) promoted noncore foods. Ads for noncore foods were more commonly delivered as video rather than overlay ads. Among ads promoting noncore foods, the most commonly employed persuasive marketing techniques found were taste appeal (42.3%), uniqueness/novelty (32.4%), the use of animation (22.5%), fun appeal (22.5%), use of promotional characters (15.5%), price (12.7%), and health and nutrition benefits (8.5%).
CONCLUSIONS: Similar to television, unhealthy food ads predominate in content aimed toward children on YouTube. Policies regulating food marketing to children need to be extended to cover online content in line with a rapidly-evolving digital media environment. Service providers of social media can play a part in limiting unhealthy food advertising to children.