OBJECTIVE: We aimed to identify a posteriori dietary patterns for Chinese, Malay, and Indian ethnic groups in an urban Asian setting, compare these with a priori dietary patterns, and ascertain associations with cardiovascular disease risk factors including hypertension, obesity, and abnormal blood lipid concentrations.

METHODS: We used cross-sectional data from 8433 Singapore residents (aged 21-94 y) from the Multi-Ethnic Cohort study of Chinese, Malay, and Indian ethnicity. Food consumption was assessed using a validated 169-item food-frequency questionnaire. With the use of 28 food groups, dietary patterns were derived by principal component analysis, and their association with cardiovascular disease risk factors was assessed using multiple linear regression. Associations between derived patterns and a priori patterns (aHEI-2010-Alternative Healthy Eating Index-2010, aMED-alternate Mediterranean Diet, and DASH-Dietary Approaches to Stop Hypertension) were assessed, and the magnitude of associations with risk factors compared.

RESULTS: We identified a "healthy" dietary pattern, similar across ethnic groups, and characterized by high intakes of whole grains, fruit, dairy, vegetables, and unsaturated cooking oil and low intakes of Western fast foods, sugar-sweetened beverages, poultry, processed meat, and flavored rice. This "healthy" pattern was inversely associated with body mass index (BMI; in kg/m2) (-0.26 per 1 SD of the pattern score; 95% CI: -0.36, -0.16), waist circumference (-0.57 cm; 95% CI: -0.82, -0.32), total cholesterol (-0.070 mmol/L; 95% CI: -0.091, -0.048), LDL cholesterol (-0.054 mmol/L; 95% CI: -0.074, -0.035), and fasting triglycerides (-0.22 mmol/L; 95% CI: -0.04, -0.004) and directly associated with HDL cholesterol (0.013 mmol/L; 95% CI: 0.006, 0.021). Generally, "healthy" pattern associations were at least as strong as a priori pattern associations with cardiovascular disease risk factors.

METHODS: Individual participant data meta-analysis included 362,114 participants (43% women), from seven prospective cohort studies, free from cancer at enrollment. The WCRF/AICR diet score was based on: (i) energy-dense foods and sugary drinks, (ii) plant foods, (iii) red and processed meat, and (iv) alcoholic drinks. Cox proportional hazards regression was used to examine the association between the diet score and cancer risks. Adjusted, cohort-specific HRs were pooled using random-effects meta-analysis. Risk advancement periods (RAP) were calculated to quantify the time period by which the risk of cancer was postponed among those adhering to the recommendations.

RESULTS: After a median follow-up of 11 to 15 years across cohorts, 70,877 cancer cases were identified. Each one-point increase in the WCRF/AICR diet score [range, 0 (no) to 4 (complete adherence)] was significantly associated with a lower risk of total cancer [HR, 0.94; 95% confidence interval (CI), 0.92-0.97], cancers of the colorectum (HR, 0.84; 95% CI, 0.80-0.89) and prostate (HR, 0.94; 95% CI, 0.92-0.97), but not breast or lung. Adherence to an additional component of the WCRF/AICR diet score significantly postponed the incidence of cancer at any site by 1.6 years (RAP, -1.6; 95% CI, -4.09 to -2.16).

CONCLUSIONS: Adherence to WCRF/AICR dietary recommendations is associated with lower risk of cancer among older adults.

METHODS: A case-control study comprising 134 breast cancer patients and 265 cancer-free controls were conducted. Dietary intakes were assessed using a validated food frequency questionnaire (FFQ), from which the HEI-2015 score was calculated. Logistic regression was used to derive the odds ratios (ORs) for measuring the association between HEI-2015 scores and breast cancer risk.

RESULTS: Subjects in the top quartile of HEI-2015 had a 46% lower chance of breast cancer compared with subjects in the bottom quartile (OR 0.54; 95% CI 0.30, 0.98). After adjustment for potential confounders such as age, age at menarche, oral contraceptive drug use, menopausal status, marital status, body mass index, smoking and education level, the association between HEI-2015 score and a lower risk of breast cancer was enhanced (OR 0.32; 95% CI 0.16, 0.65).

METHODS: The HD-HEI tool adapted the Malaysian Dietary Guidelines 2010 framework according to HD-specific nutrition guidelines. This HD-HEI was applied to 3-day dietary records of 382 HD patients. Relationships between HD-HEI scores and nutritional parameters were tested by partial correlations. Binary logistic regression models adjusted with confounders were used to determine adjusted odds ratio (adjOR) with 95% confidence interval (CI) for nutritional risk based on HD-HEI scores categorization.

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.

SUBJECTS/METHODS: The height, weight, and WC of four-hundred-and-ninety adults (n = 490) in Malaysia were measured using standard procedures. The three-day 24-hour dietary recalls were conducted on 422 out of the 490 adults and their dietary intakes were evaluated in detail. The selected dietary intake variables were used to determine the associations with the obesity indicators.

RESULTS: Among the participants, 52.8% were overweight or obese. After data analysis, the mean energy intake was 1,550 kcal/day, in which male participants had a significantly higher energy and macronutrients intake than females. Protein consumption and its percentage of energy contribution exceeded the recommended range. The consumption of fruits, vegetables, and milk and milk products were lower than the recommended number of servings for a healthy diet. The male participants consumed significantly more servings of carbohydrate-based foods, meat, and fats, oils, and sweets than females. Among the selected dietary intake variables, only the carbohydrate intake was negatively associated with the BMI (Estimate b = -0.008) and WC measurements (Estimate b = -0.019) after adjusting for covariates.

METHODS AND ANTICIPATED RESULTS: A cluster randomized controlled study will be conducted, involving 250 Middle Eastern adolescents, in Arabic schools in Malaysia. The participants will be randomly assigned to the intervention and control groups. While the intervention group participates in six weeks of fortnightly six sessions (45 minutes per session), the control group will carry on with their regular curriculums, and normal physical activity routines. The variables which will be evaluated include anthropometric measurements, knowledge, attitude, daily routines, physical activity, sedentary behaviour, food assessment, eating attitudes test-26, and a structured questionnaire based on the HBM. Data will be collected from the intervention and control groups at baseline, post-intervention, and two months following the intervention. Data analysis will be performed by way of the SPSS Statistics software version 26. The generalized estimating equation (GEE) will be used, to test the effect of the intervention program, with regards to the selected variables (outcomes), between and within-group at baseline, as well as six weeks and two months following intervention, after adjusting for clustering. Outcomes will be assessed at each time point, along with a derived average over all three-time points; thus, ensuring that both the cumulative and overall effects are determined.

CONCLUSIONS: This trial will provide useful information for improving the knowledge, attitude, and practices of Middle Eastern adolescents, with regards to body weight status, physical activity level, nutrition status (BMI and dietary intake), and disordered eating. This will go a long way, towards ensuring their adherence to appropriate physical activities, and a healthy diet, to keep non-communicable diseases at bay.