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: 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.
METHODOLOGY: A multiethnic cross-sectional national cohort (N = 7198) of the Singapore general population consisting of Chinese (N = 4873), Malay (N = 1167) and Indian (N = 1158) adults were evaluated using measures of HRQoL (SF-36 version 2), family functioning, health behaviours and clinical/laboratory assessments. Multiple regression analyses were performed to identify determinants of physical and mental HRQoL in the overall population and their potential differential effects by ethnicity. No a priori hypotheses were formulated so all interaction effects were explored.
PRINCIPAL FINDINGS: HRQoL levels differed between ethnic groups. Chinese respondents had higher physical HRQoL (PCS) than Indian and Malay participants (p<0.001) whereas mental HRQoL (MCS) was higher in Malay relative to Chinese participants (p<0.001). Regressions models explained 17.1% and 14.6% of variance in PCS and MCS respectively with comorbid burden, income and employment being associated with lower HRQoL. Age and family were associated only with MCS. The effects of gender, stroke and musculoskeletal conditions on PCS varied by ethnicity, suggesting non-uniform patterns of association for Chinese, Malay and Indian individuals.
CONCLUSIONS: Differences in HRQoL levels and determinants of HRQoL among ethnic groups underscore the need to better or differentially target population segments to promote well-being. More work is needed to explore HRQoL and wellness in relation to ethnicity.
OBJECTIVE: We examined whether adipocytokines might explain the ethnic differences in the relationship between obesity and insulin resistance among the three major ethnic groups in Singapore.
DESIGN AND PARTICIPANTS: This was a cross-sectional study of 101 Chinese, 82 Malays, and 81 South Asian men. Insulin sensitivity index (ISI) was measured using hyperinsulinemic euglycemic clamp. Visceral (VAT) and subcutaneous adipose tissue (SAT) volumes were quantified using magnetic resonance imaging.
MAIN OUTCOME MEASURES: Plasma total and high-molecular-weight adiponectin, leptin, visfatin, apelin, IL-6, fibroblast growth factor 21 (FGF21), retinol binding protein-4 (RBP 4), and resistin were measured using enzyme-linked immunoassays.
RESULTS: Principle component (PC) analysis on the adipocytokines identified three PCs, which explained 49.5% of the total variance. Adiponectin loaded negatively, and leptin and FGF21 loaded positively onto PC1. Visfatin, resistin, and apelin all loaded positively onto PC2. IL-6 loaded positively and RBP-4 negatively onto PC3. Only PC1 was negatively associated with ISI in all ethnic groups. In the path analysis, SAT and VAT were negatively associated with ISI in Chinese and Malays without significant mediatory role of PC1. In South Asians, the relationship between VAT and ISI was mediated partly through PC1, whereas the relationship between SAT and ISI was mediated mainly through PC1.
CONCLUSIONS: The relationships between abdominal obesity, adipocytokines and insulin sensitivity differ between ethnic groups. Adiponectin, leptin, and FGF21 play a mediating role in the relationship between abdominal adiposity and insulin resistance in South Asians, but not in Malays or Chinese.