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.
CONCLUSION: A healthful dietary pattern that correlated well with a priori patterns and was associated with lower BMI, serum LDL cholesterol, total cholesterol, and fasting triglyceride concentrations was identified across 3 major Asian ethnic groups.
METHODS: A sample of 3895 individuals without known diabetes underwent detailed interview and health examination, including anthropometric and biochemical evaluation, between 2004 and 2007. Pearson's correlation, analysis of variance and multiple linear regression analyses were used to examine the influence of ethnicity on HbA(1c) .
RESULTS: As fasting plasma glucose increased, HbA(1c) increased more in Malays and Indians compared with Chinese after adjustment for age, gender, waist circumference, serum cholesterol, serum triglyceride and homeostasis model assessment of insulin resistance (P-interaction < 0.001). This translates to an HbA(1c) difference of 1.1 mmol/mol (0.1%, Indians vs. Chinese), and 0.9 mmol/mol (0.08%, Malays vs. Chinese) at fasting plasma glucose 5.6 mmol/l (the American Diabetes Association criterion for impaired fasting glycaemia); and 2.1 mmol/mol (0.19%, Indians vs. Chinese) and 2.6 mmol/mol (0.24%, Malays vs. Chinese) at fasting plasma glucose 7.0 mmol/l, the diagnostic criterion for diabetes mellitus.
CONCLUSIONS: Using HbA(1c) in place of fasting plasma glucose will reclassify different proportions of the population in different ethnic groups. This may have implications in interpretation of HbA(1c) results across ethnic groups and the use of HbA(1c) for diagnosing diabetes mellitus.
METHODS AND RESULTS: Blood pressures, fasting lipid profile and fasting glucose were measured, and DASH score was computed based on a 22-item food frequency questionnaire. Older individuals, women, those not consuming alcohol and those undertaking regular physical activity were more likely to have higher DASH scores. In the Malaysian cohort, while total DASH score was not significantly associated with cardio-metabolic risk factors after adjusting for confounders, significant associations were observed for intake of green vegetable [0.011, standard error (SE): 0.004], and red and processed meat (-0.009, SE: 0.004) with total cholesterol. In the Philippines cohort, a 5-unit increase in total DASH score was significantly and inversely associated with systolic blood pressure (-1.41, SE: 0.40), diastolic blood pressure (-1.09, SE: 0.28), total cholesterol (-0.015, SE: 0.005), low-density lipoprotein cholesterol (-0.025, SE: 0.008), and triglyceride (-0.034, SE: 0.012) after adjusting for socio-demographic and lifestyle groups. Intake of milk and dairy products, red and processed meat, and sugared drinks were found to significantly associated with most risk factors.
CONCLUSIONS: Differential associations of DASH diet and dietary components with cardio-metabolic risk factors by country suggest the need for country-specific tailoring of dietary interventions to improve cardio-metabolic risk profiles.
METHODS: This study included 1740 males (1146 Chinese, 327 Malays and 267 Asian Indians) and 1950 females (1329 Chinese, 360 Malays and 261 Asian Indians) with complete data on anthropometric indices, fasting lipids, smoking status, alcohol consumption, exercise frequency and genotype at the APOE locus.
RESULTS: Malays and Asian Indians were more obese compared with the Chinese. Smoking was uncommon in all females but Malay males had significantly higher prevalence of smokers. Malays had the highest LDL-C whilst Indians had the lowest HDL-C, The epsilon 3 allele was the most frequent allele in all three ethnic groups. Malays had the highest frequency of epsilon 4 (0.180 and 0.152) compared with Chinese (0.085 and 0.087) and Indians (0.108 and 0.075) in males and females, respectively. The epsilon 2 allele was the least common in Asian Indians. Total cholesterol (TC) and LDL-C was highest in epsilon 4 carriers and lowest in epsilon 2 carriers. The reverse was seen in HDL-C with the highest levels seen in epsilon 2 subjects. The association between ethnic group and HDL-C differed according to APOE genotype and gender. Asian Indians had the lowest HDL-C for each APOE genotype except in Asian Indian males with epsilon 2, where HDL-C concentrations were intermediate between Chinese and Malays.
CONCLUSION: Ethnic differences in lipid profile could be explained in part by the higher prevalence of epsilon 4 in the Malays. Ethnicity may influence the association between APOE genotypes and HDL-C. APOE genotype showed no correlation with HDL-C in Malay males whereas the association in Asian Indians was particularly marked. Further studies of interactions between genes and environmental factors will contribute to the understanding of differences of coronary risk amongst ethnic groups.