A Study on the Factors Influencing Triglyceride Levels among Adults in Northeast China

Zhang, Anning; Yao, Yan; Xue, Zhiqiang; Guo, Xin; Dou, Jing; Lv, Yaogai; Shen, Li; Yu, Yaqin; Jin, Lina

doi:10.1038/s41598-018-24230-4

Cited by 18 publications

(13 citation statements)

References 32 publications

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“…Based on the results, simple Cox regression tagged baseline lipoproteins including TG, HDL-C, and LDL-C as predictors, which was a reasonable result because plasma lipoproteins currently lead to abnormal future blood lipids. In addition, the HRs of these predictors were comparable to those of other association studies [9,[30][31][32][33][34]. Correspondingly, the HRs of these 7 variables were also consistent with those in early published studies of dyslipidaemia prediction models [16,18,19].…”

Section: Discussionsupporting

confidence: 86%

Genetic factors increase the identification efficiency of predictive models for dyslipidaemia: a prospective cohort study

et al. 2021

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Background Few studies have developed risk models for dyslipidaemia, especially for rural populations. Furthermore, the performance of genetic factors in predicting dyslipidaemia has not been explored. The purpose of this study is to develop and evaluate prediction models with and without genetic factors for dyslipidaemia in rural populations. Methods A total of 3596 individuals from the Henan Rural Cohort Study were included in this study. According to the ratio of 7:3, all individuals were divided into a training set and a testing set. The conventional models and conventional+GRS (genetic risk score) models were developed with Cox regression, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) classifiers in the training set. The area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination index (IDI) were used to assess the discrimination ability of the models, and the calibration curve was used to show calibration ability in the testing set. Results Compared to the lowest quartile of GRS, the hazard ratio (HR) (95% confidence interval (CI)) of individuals in the highest quartile of GRS was 1.23(1.07, 1.41) in the total population. Age, family history of diabetes, physical activity, body mass index (BMI), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were used to develop the conventional models, and the AUCs of the Cox, ANN, RF, and GBM classifiers were 0.702(0.673, 0.729), 0.736(0.708, 0.762), 0.787 (0.762, 0.811), and 0.816(0.792, 0.839), respectively. After adding GRS, the AUCs increased by 0.005, 0.018, 0.023, and 0.015 with the Cox, ANN, RF, and GBM classifiers, respectively. The corresponding NRI and IDI were 25.6, 7.8, 14.1, and 18.1% and 2.3, 1.0, 2.5, and 1.8%, respectively. Conclusion Genetic factors could improve the predictive ability of the dyslipidaemia risk model, suggesting that genetic information could be provided as a potential predictor to screen for clinical dyslipidaemia. Trial registration The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register. (Trial registration: ChiCTR-OOC-15006699. Registered 6 July 2015 - Retrospectively registered).

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Section: Discussionsupporting

confidence: 86%

Genetic factors increase the identification efficiency of predictive models for dyslipidaemia: a prospective cohort study

et al. 2021

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“…Controlling high triglyceride levels is important, especially in females, because high TG levels are not only associated with coronary artery disease but also prone to become deranged during conditions such as pregnancy, hormonal changes, and weight gain [41]. The findings in Fig.…”

Section: Discussionmentioning

confidence: 92%

Association between standardized vitamin 25(OH)D and dyslipidemia: a community-based study in Riyadh, Saudi Arabia

AlQuaiz

Kazi

Youssef

et al. 2020

Environ Health Prev Med

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Background: Vitamin D deficiency associated with dyslipidemia can contribute towards cardiovascular diseases. Previous studies have found that Saudi Arabia has a high burden of vitamin D deficiency and cardiovascular disease risk factors. We aimed to explore the relationship between vitamin D deficiency and dyslipidemia, including total cholesterol, low-density lipids, high-density lipids (HDL), and triglycerides (TG) in apparently healthy Saudi male and female participants aged 30-75 years. Methods: A cross-sectional study was conducted on 1717 apparently healthy Saudi participants from 18 primary health care centers in Riyadh. Data collectors conducted the interviews, took anthropometric measurements, and collected the blood samples. Serum 25-hydroxyvitamin vitamin D (25(OH)D) levels were measured using an electrochemiluminescence assay method. Lipid panel was measured by a fully automated analyzer using enzymatic methods. Results: Multivariable logistic regression analysis revealed that the adjusted odds ratio (OR A) of low level of HDL cholesterol in association with 25(OH)D deficiency was 2.1 times higher in males (OR A = 2.1; 95% CI = 1.1, 3.9) and 1.3 times higher in females (OR A = 1.3; 95% CI = 0.9, 1.9). A significant excess odds ratio of high levels of TG in association with 25(OH) D deficiency was observed in females (OR A = 3.0; 95% CI = 1.1, 7.9) but not in males. Conclusion: Vitamin D deficiency is highly prevalent in Saudi Arabia. Low levels of HDL cholesterol in men and high TG levels in women are associated with vitamin D deficiency. The results emphasize the importance of treating vitamin D deficiency in the general population.

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“…Our finding that low DD was associated with elevated TG concentrations is similar to a cross-sectional study in Iranian adults [ 17 ]. There are many factors other than DD that may influence serum TG concentrations, such as consumption of sugary food and drinks, saturated and trans-fats, refined grains, high energy foods as well as alcohol [ 59 ] and overweight and obesity and tobacco use [ 60 ].…”

Section: Discussionmentioning

confidence: 99%

Dietary Diversity and its Association with Nutritional Status, Cardiometabolic Risk Factors and Food Choices of Adults at Risk for Type 2 Diabetes Mellitus in Cape Town, South Africa

et al. 2022

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In South Africa, the nutrition transition has led to unhealthy diets lacking variety, contributing to the rise in overweight, obesity and diet-related noncommunicable diseases. Using baseline screening data of the South African Diabetes Prevention Programme (SA-DPP) study, this study aims to determine the relationship of dietary diversity (DD) with nutritional status, cardiometabolic risk factors and food choices of adults at risk of type 2 diabetes in resource-poor communities around Cape Town. Data of 693 adults, 25–65 years old were analysed. This included socio-demographic information, anthropometric measurements, biochemical assessments, food groups consumed the previous day and consumption frequency of certain foods to reflect food choices. The Minimum Dietary Diversity for Women (MDD-W) indicator was calculated; 70.4% of participants had low DD (<5 food groups). Low DD was associated with elevated serum triglycerides [AOR: 1.49, 95% CI (1.03, 2.15) p = 0.036]. The DD score was positively correlated (although weak) with the unhealthy food score (r = 0.191, p = 0.050) and sugary food score (r = 0.139, p < 0.01). Study participants at risk of diabetes consumed a diet low in DD; however, DD was not associated with nutritional status or cardiometabolic risk factors except for serum triglycerides.

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A Study on the Factors Influencing Triglyceride Levels among Adults in Northeast China

Cited by 18 publications

References 32 publications

Genetic factors increase the identification efficiency of predictive models for dyslipidaemia: a prospective cohort study

Genetic factors increase the identification efficiency of predictive models for dyslipidaemia: a prospective cohort study

Association between standardized vitamin 25(OH)D and dyslipidemia: a community-based study in Riyadh, Saudi Arabia

Dietary Diversity and its Association with Nutritional Status, Cardiometabolic Risk Factors and Food Choices of Adults at Risk for Type 2 Diabetes Mellitus in Cape Town, South Africa

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