DESIGN AND METHODS: The respondents (n=30) were conveniently recruited within 10 kilometres radius of Kuantan city. The data were obtained using semi-guided administered questionnaires, which consists of four parts: socio-demographic data, lifestyle and clinical history (Part A); attitude and awareness on dietary practice regarding urolithiasis (Part B); food frequency questionnaire on urolithiasis (Part C) and level of knowledge on urolithiasis (Part D).
RESULTS: Majority of the respondents were women (70%), Malay (83.3%), mean age of 33.97 (±9.27), married (63.3%), completed higher education level (60%), working with government sector (33.3%) and have fixed monthly income (53.3%). Some of them had hypertension (n=4), diabetes (n=1), gout (n=1) and intestinal problem (n=1). Majority (80%) claimed having no family history of urolithiasis, consumed alcohol (10%), exercise with average frequency 2-3 times/week (46.7%) and heard about urolithiasis from healthcare worker (46.7%). The respondents' awareness about urolithiasis is considered to be good [81.23 (±9.98)] but having poor knowledge score [2.70 (±1.149)]. Majority preferred wholemeal bread, white rice, chicken meat, mackerel fish, chicken egg, apple, carrot, mustard leave and fresh milk in daily intake. Lesser plain water intake than standard requirement was noticed among respondents. Seasoning powder was commonly used for seasoning.
CONCLUSIONS: Generally, the general population of Kuantan, Pahang was aware of urolithiasis disease but needed more information on dietary aspect in terms of knowledge and food choice.
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.
DESIGN: This was a cross-sectional study conducted between August 2008 and August 2009 using three methods: interviews, focus group discussions and analyses of government reports.
SETTING: The study was conducted in rural and urban areas in Manila and Calabanga (Philippines), Selangor and Kuala Selangor (Malaysia), and Padang, Pariaman Tanah Datar and Limapuluh Kota (West Sumatra, Indonesia).
SUBJECTS: Adults aged 18 to 77 years.
RESULTS: The results showed that Filipinos, Malaysians and Indonesians have retained many aspects of their traditional diets. In fact, most participants in the study considered Western-style and franchise fast foods as snack or recreational foods to be consumed once in a while only. However, a significant difference was noted between urban and rural areas in food varieties consumed. Participants in urban areas consumed more varieties of traditional foods owing to their availability and the participants’ food purchasing power. Although traditional food patterns were maintained by most of the participants, more sugar and vegetable oils were consumed and added to the traditional recipes.
CONCLUSIONS: The rapid nutrition transition in this region may be due, instead, to increasing food availability and food purchasing power, rather than to a shift in food preferences towards modern Western foods.
OBJECTIVE: To characterize and evaluate the plant-based alternatives available on the market in Spain in comparison to animal products in terms of their nutritional composition and profile, and degree of processing.
METHODS: Nutritional information for PBAPs and homologs were obtained from the Spanish 'Veggie base', branded food composition database. Five PBAPs categories (cheese, dairy products, eggs, meat, and fish, n = 922) were compared to animal-based processed (n = 922) and unprocessed (n = 381) homologs, using the modified version of the Food Standard Agency Nutrient Profiling System (FSAm-NPS score) and NOVA classification criteria.
RESULTS: Compared to processed or unprocessed animal food, PBAPs contain significantly higher sugar, salt, and fiber. PBAPs for fish, seafood, and meat were lower in protein and saturated fatty acids. Overall, 68% of PBAPs, 43% of processed and 75% of unprocessed animal-homologs had Nutri-Score ratings of A or B (most healthy). About 17% of PBAPs, 35% of processed and 13% of unprocessed animal-based food were in Nutri-Score categories D or E (least healthy). Dairy, fish, and meat alternatives had lower FSAm-NPS scores (most healthy), while cheese alternatives scored higher (least healthy) than animal-based homologs. Unprocessed fish and meat were healthier than similar PBAPs based on FSAm-NPS criteria. Approximately 37% of PBAPs and 72% of processed animal-based products were ultra-processed food (NOVA group 4). Within the ultra-processed food group, Nutri-Score varied widely.
CONCLUSIONS: Most PBAPs had better nutrient profile than animal-based homologs. However, cheese, fish and meats PBAPs had poorer nutrient profile and were more processed. Given the high degree of processing and variable nutritional profile, PBAPs require a multi-dimensional evaluation of their health impact.
METHODS: Therefore, using linear programming, this study is aimed to develop a healthy and balanced menu with minimal cost in accordance to individual needs that could in return help to prevent cancer. A cross sectional study involving 100 adults from a local university in Kuala Lumpur was conducted in 3 phases. The first phase is the data collection for the subjects, which includes their socio demographic, anthropometry and diet recall. The second phase was the creation of a balanced diet model at a minimum cost. The third and final phase was the finalization of the cancer prevention menu. Optimal and balanced menus were produced based on respective guidelines of WCRF/AICR (World Cancer Research Fund/ American Institute for Cancer Research) 2007, MDG (Malaysian Dietary Guidelines) 2010 and RNI (Recommended Nutrient Intake) 2017, with minimum cost.
RESULTS: Based on the diet recall, most of subjects did not achieve the recommended micronutrient intake for fiber, calcium, potassium, iron, B12, folate, vitamin A, vitamin E, vitamin K, and beta-carotene. While, the intake of sugar (51 ± 19.8 g), (13% ± 2%) and sodium (2585 ± 544 g) was more than recommended. From the optimization model, three menus, which met the dietary guidelines for cancer prevention by WCRF/AICR 2007, MDG 2010 and RNI 2017, with minimum cost of RM7.8, RM9.2 and RM9.7 per day were created.
CONCLUSION: Linear programming can be used to translate nutritional requirements based on selected Dietary Guidelines to achieve a healthy, well-balanced menu for cancer prevention at minimal cost. Furthermore, the models could help to shape consumer food choice decision to prevent cancer especially for those in low income group where high cost for health food has been the main deterrent for healthy eating.