Socio-economic status and serum lipids: a cross-sectional study in a Chinese urban population. 2002

Zhijie Yu, and Aulikki Nissinen, and Erkki Vartiainen, and Gang Hu, and Huiguang Tian, and Zeyu Guo
Department of Public Health and General Practice, University of Kuopio, Kuopio, Finland.

Socio-economic status and serum lipids are important factors in the progression of cardiovascular disease. We studied the association between socio-economic status and serum lipids in a Chinese urban population. In all, 4,541 respondents (2,231 men and 2,310 women) between 25-64 years of age participated in a cross-sectional population survey carried out in Tianjin, China, and provided blood samples. Three socio-economic indicators (education, occupation, and income), total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides were determined. People in higher socio-economic groups had a more unfavorable serum lipid profile compared with those in lower socio-economic groups. This significant association was especially apparent in men. Education seemed to be the most important predictor of serum lipids in the three socio-economic indicators. The direction of the association between high socio-economic status and poor serum lipid profiles appears to be opposite to those observed in the developed countries.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009790 Occupations Crafts, trades, professions, or other means of earning a living. Vocations,Occupation,Vocation
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002681 China A country spanning from central Asia to the Pacific Ocean. Inner Mongolia,Manchuria,People's Republic of China,Sinkiang,Mainland China
D002784 Cholesterol The principal sterol of all higher animals, distributed in body tissues, especially the brain and spinal cord, and in animal fats and oils. Epicholesterol
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults

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