BWBrendon Yi Neng Wong
Brendon Yi Neng Wong
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Brendon Yi Neng Wong has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Irving Yu Le Shua
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication - Jimmy Lee
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
1 shared publication - John Campbell Chambers
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication - Kaleeswaran Shaminidevi
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication - Max Lam
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication - Nadia Loh Ting Wei
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
1 shared publication
Latest Publications
- Open Access
The Development and Validation of the Food Memory Bias Test for a Large-Scale Epidemiological Study in a Multiethnic Asian Population
Background: Memory influences decision-making regarding eating behaviour. However, marketing utilises our memory to exploit our consumptive habits. Whether we have an inherent bias towards memorising visual cues associated with high-calorie foods and how such bias contributes to our health outcomes remains to be determined. We therefore aimed to develop and validate a computerized, image-based Food Memory Bias Task (FMBT) for use in multiethnic Asian populations. Methods: In the development phase involving 172 participants, 91.9% rated the instrument as user-friendly and we optimised the instrument format into 12 visual food cues and 30-min delay period to avoid a ceiling effect. In the validation phase involving 184 multi-ethnic Asian participants (49.3 (14.5) years old, 44.6% male, 71.7% Chinese), FMBT memory score was associated with the brief assessment of cognition memory (β(p) = 0.23 (5.1 × 10−6)), and general cognition score ‘g’ (β(p) = 0.30 (6.5 × 10−9)). Results: Higher memory bias was associated with lower memory score in the low-calorie bias group (, ), but not in the hig h-calorie bias group. In this present study, despite randomly administering two versions of the test across visits, the FMBT bias score demonstrates a significant learning effect and low reproducibility (r(p) = −0.14 (0.11) across visits). Food memory bias score is associated with higher food approach traits according to the Adult-Eating Behaviour Questionnaire (β(p) = 0.23(0.015)), independent of age, sex, and ethnicity. Conclusion: FMBT provides an opportunity to address epidemiological questions on how food memory bias influences dietary habit and cardiometabolic health, and how it is in turn shaped by our built environment.Open AccessThe Development and Validation of the Food Memory Bias Test for a Large-Scale Epidemiological Study in a Multiethnic Asian Population
Background: Memory influences decision-making regarding eating behaviour. However, marketing utilises our memory to exploit our consumptive habits. Whether we have an inherent bias towards memorising visual cues associated with high-calorie foods and how such bias contributes to our health outcomes remains to be determined. We therefore aimed to develop and validate a computerized, image-based Food Memory Bias Task (FMBT) for use in multiethnic Asian populations. Methods: In the development phase involving 172 participants, 91.9% rated the instrument as user-friendly and we optimised the instrument format into 12 visual food cues and 30-min delay period to avoid a ceiling effect. In the validation phase involving 184 multi-ethnic Asian participants (49.3 (14.5) years old, 44.6% male, 71.7% Chinese), FMBT memory score was associated with the brief assessment of cognition memory (β(p) = 0.23 (5.1 × 10−6)), and general cognition score ‘g’ (β(p) = 0.30 (6.5 × 10−9)). Results: Higher memory bias was associated with lower memory score in the low-calorie bias group (, ), but not in the hig h-calorie bias group. In this present study, despite randomly administering two versions of the test across visits, the FMBT bias score demonstrates a significant learning effect and low reproducibility (r(p) = −0.14 (0.11) across visits). Food memory bias score is associated with higher food approach traits according to the Adult-Eating Behaviour Questionnaire (β(p) = 0.23(0.015)), independent of age, sex, and ethnicity. Conclusion: FMBT provides an opportunity to address epidemiological questions on how food memory bias influences dietary habit and cardiometabolic health, and how it is in turn shaped by our built environment.