Can dietary factors explain differences in serum cholesterol profiles among different ethnic groups (Chinese, Malays and Indians) in Singapore?
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M Deurenberg-Yap1, T Li, W L Tan
1Department of Nutrition, Ministry of Health, Singapore. mabel_yap@moh.gov.sg
Abstract:
In Singapore. there exists differences in risk factors for coronary heart disease among the three main ethnic groups: Chinese, Malays and Indians. This study aimed to investigate if differences in dietary intakes of fat, types of fat, cholesterol, fruits, vegetables and grain foods could explain the differences in serum cholesterol levels between the ethnic groups. A total of 2408 adult subjects (61.0% Chinese, 21.4% Malays and 17.6% Indians) were selected systematically from the subjects who took part in the National Health Survey in 1998. The design of the study was based on a cross-sectional study. A food frequency questionnaire was used to assess intakes of energy, total fat, saturated fat, polyunsaturated fat, monounsaturated fat, cholesterol, fruits, vegetables and cereal-based foods. The Hegsted score was calculated. Serum total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol were analysed and the ratio of total cholesterol to high density lipoprotein cholesterol was computed. The results showed that on a group level (six sex-ethnic groups), Hegsted score, dietary intakes of fat, satutrated fat, cholesterol, vegetables and grain foods were found to be correlated to serum cholesterol levels. However, selected dietary factors did not explain the differences in serum cholesterol levels between ethnic groups when multivariate regression analysis was performed, with adjustment for age, body mass index, waist-hip ratio, cigarette smoking, occupation, education level and physical activity level. This cross-sectional study shows that while selected dietary factors are correlated to serum cholesterol at a group level, they do not explain the differences in serum cholesterol levels between ethnic groups independently of age, obesity, occupation, educational level and other lifestyle risk factors.
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