Qiufen Sun1, Qiaorui Wen1, Jun Lyu1, Dianjianyi Sun1, Yuan Ma2, Sailimai Man3, Jianchun Yin4, Cheng Jin2, Mingkun Tong2, Bo Wang2, Canqing Yu5, Yi Ning6, Liming Li1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Health Science Center Meinian Public Health Institute, Beijing 100191, China. 2. Meinian Institute of Health, Beijing 100191, China; Peking University Health Science Center Meinian Public Health Institute, Beijing 100191, China. 3. Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Meinian Institute of Health, Beijing 100191, China. 4. Meinian Institute of Health, Beijing 100191, China. 5. Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China; Peking University Health Science Center Meinian Public Health Institute, Beijing 100191, China. Electronic address: yucanqing@pku.edu.cn. 6. Meinian Institute of Health, Beijing 100191, China; Peking University Health Science Center Meinian Public Health Institute, Beijing 100191, China. Electronic address: yi.ning@meinianresearch.com.
Abstract
BACKGROUND AND AIMS: Diet can affect cardiovascular health by changing lipid profiles or obesity levels. However, the association of dietary patterns reflecting lipid metabolism and adiposity measures with cardiovascular disease (CVD) is unclear. This study aimed to derive dietary patterns that explained variation in blood lipids and adiposity and investigate their associations with prevalent CVD. METHODS AND RESULTS: A cross-sectional study was constructed in Beijing MJ Health Screening Center from 2008 to 2018. A dietary pattern was derived using reduced-rank regression among 75,159 participants without CVD. The dietary pattern explained the largest in predicting lipid profiles and adiposity measures. The dietary pattern was associated with a higher level of LDL-cholesterol and triglyceride, and high body mass index and waist circumference, but lower HDL-cholesterol. The dietary pattern was characterized by high intakes of staple food, red meat, processed food, fried food, edible offal, and less intakes of jam or honey, fruits, milk, and dairy products. Among 89,633 participants, we evaluated its association with prevalent CVD using multivariate logistic regression with adjustment for age, sex, annual income, education attainment, marital status, family history of CVD, smoking status, alcohol use, physical activity, and daily energy intake. Individuals with the highest quintile of dietary pattern score were 1%-38% more likely to have prevalent CVD than the lowest quintile (OR = 1.18, 95% CI = 1.01-1.38). CONCLUSION: A diet pattern reflecting lipid profiles and obesity level was positively related to prevalent CVD, which could provide new insights in optimizing blood lipids and body shape for the prevention of CVD through dietary approaches among the Chinese population.
BACKGROUND AND AIMS: Diet can affect cardiovascular health by changing lipid profiles or obesity levels. However, the association of dietary patterns reflecting lipid metabolism and adiposity measures with cardiovascular disease (CVD) is unclear. This study aimed to derive dietary patterns that explained variation in blood lipids and adiposity and investigate their associations with prevalent CVD. METHODS AND RESULTS: A cross-sectional study was constructed in Beijing MJ Health Screening Center from 2008 to 2018. A dietary pattern was derived using reduced-rank regression among 75,159 participants without CVD. The dietary pattern explained the largest in predicting lipid profiles and adiposity measures. The dietary pattern was associated with a higher level of LDL-cholesterol and triglyceride, and high body mass index and waist circumference, but lower HDL-cholesterol. The dietary pattern was characterized by high intakes of staple food, red meat, processed food, fried food, edible offal, and less intakes of jam or honey, fruits, milk, and dairy products. Among 89,633 participants, we evaluated its association with prevalent CVD using multivariate logistic regression with adjustment for age, sex, annual income, education attainment, marital status, family history of CVD, smoking status, alcohol use, physical activity, and daily energy intake. Individuals with the highest quintile of dietary pattern score were 1%-38% more likely to have prevalent CVD than the lowest quintile (OR = 1.18, 95% CI = 1.01-1.38). CONCLUSION: A diet pattern reflecting lipid profiles and obesity level was positively related to prevalent CVD, which could provide new insights in optimizing blood lipids and body shape for the prevention of CVD through dietary approaches among the Chinese population.