SUBJECTS/METHODS: A taste database including 467 foods' sweet, sour, bitter, salt, umami and fat sensation values was combined with food intake data to assess dietary taste patterns: the contribution to energy intake of 6 taste clusters. The FFQ's reliability was assessed against 3-d 24hR and urinary biomarkers for sodium (Na) and protein intake (N) in Dutch men (n = 449) and women (n = 397) from the NQplus validation study (mean age 53 ± 11 y, BMI 26 ± 4 kg/m2).

METHODS: A systematic search of Medline via the PubMed, Science Direct, Cochrane Review and Web of Science databases was conducted for studies on the associations between diet and PA factors and cardio-metabolic risk factors among Malaysian adolescents aged 13-18 years that were published until 31 August 2017. The search results were independently screened and extracted by two reviewers.

RESULTS: From over 2,410 references retrieved, 20 full texts articles were screened as potentially relevant. Seventeen (16 cross-sectional and one intervention) met the inclusion criteria for data extraction and analysis. All 17 studies were rated as poor quality and the majority had made insufficient adjustment for confounders. As regards the effect of diet and PA on cardio-metabolic health, the intakes of energy (n = 4) and macronutrients (n = 3) and meal frequency (n = 5) were the most commonly studied dietary factors, while the PA score and level were the most commonly studied PA factors. In addition, BMI and body weight were the most common cardio-metabolic health outcomes. The studies showed that obese and overweight adolescents consume significantly more energy and macronutrients. They are also more likely to skip their daily meals compared to their normal weight peers. In most studies, the direction of the PA effect on body weight was unclear. Some studies found that higher PA is associated with a lower risk of overweight and obesity. However, the associations are often small or inconsistent, with few studies controlling for confounding factors.

METHODS: A cross-sectional questionnaire survey and anthropometric measurement were conducted with undergraduate university students that were randomly recruited. The Eating Attitudes Test (EAT-26) was utilized to determine the prevalence of disordered eating attitudes. The sample included 3148 university students, with a mean age of 20.5 years, SD = 1.6.

RESULTS: Using the EAT-26, 11.5% of the students across all countries were classified as being at risk for an eating disorder, ranging from below 10% in Indonesia, Thailand and Vietnam to 13.8% in Malaysia and 20.6% in Myanmar. In multivariable logistic regression analysis, sociodemographic factors (wealthier subjective economic status, and living in a lower middle income country), underweight and overweight body weight perception, psychological factors (depression symptoms and pathological internet use), and being obese were associated with eating disorder risk.

CONCLUSIONS: Relatively high rates of eating disorder risk were found. This result calls for increased awareness, understanding of eating disorders and related risk factors and interventions in university students in ASEAN.

METHODS AND STUDY DESIGN: Eating behaviors namely Cognitive Restraint, Uncontrolled Eating and Emotional Eating scores were assessed by the Three Factor Eating Questionnaire-R18. The preference/intake frequency/craving of 26 common high-fat Malaysian foods was assessed using a 7-point hedonic scale. Anthropometric measurements were taken and Taq1 gene polymorphisms were genotyped by PCR-Restriction Fragment Length Polymorphism using DNA extracted from mouthwash samples.

RESULTS: The overall minor allele frequencies of Taq1A, Taq1B and Taq1D according to ethnicities (Chinese/Indian) were 0.37/0.29, 0.39/0.28, 0.06/0.30, respectively; genotype and allele distributions of Taq1B and Taq1D were significantly different between ethnicities. Eating behaviorscores were not significantly different between gender and ethnicities. Those with A1 or B1 allele had lower Cognitive Restraint score and higher Uncontrolled Eating score, while those with A1/A1 or B1/B1 genotype had higher fast food preference. D1 allele was associated with increased starchy food craving and mamak (Malaysian Indian-Muslim) food preference, but not eating behavior scores. All three gene variants were not associated with obesity and adiposity.