Comparison of non-HDL cholesterol and waist circumference vs. triglyceride levels and waist circumference in predicting coronary heart disease risk

BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.

The association between maternity insurance, residence status and selected perinatal outcomes among Chinese women

Objective: To investigate the impact of maternity insurance and maternal residence on birth outcomes in a Chinese population. Methods: Secondary data was analyzed from a perinatal cohort study conducted in the Beichen District of the city of Tianjin, China. A total of 2364 pregnant women participated in this study at approximately 12-week gestation upon registration for receiving prenatal care services. After accounting for missing information for relevant variables, a total of 2309 women with single birth were included in this analysis. Results: A total of 1190 (51.5%) women reported having maternity insurance, and 629 (27.2%) were rural residents. The abnormal birth outcomes were small for gestational age (SGA, n=217 (9.4%)), large for gestational age (LGA, n=248 (10.7%)), birth defect (n=48 (2.1%)) including congenital heart defect (n=32 (1.4%)). In urban areas, having maternal insurance increased the odds of SGA infants (1.32, 95%CI (0.85, 2.04), NS), but decreased the odds of LGA infants (0.92, 95%CI (0.62, 1.36), NS); also decreased the odds of birth defect (0.93, 95%CI (0.37, 2.33), NS), and congenital heart defect (0.65, 95%CI (0.21, 1.99), NS) after adjustment for covariates. In contrast to urban areas, having maternal insurance in rural areas reduced the odds of SGA infants (0.60, 95%CI (0.13, 2.73), NS); but increased the odds of LGA infants (2.16, 95%CI (0.92, 5.04), NS), birth defects (2.48, 95% CI (0.70, 8.80), NS), and congenital heart defect (2.18, 95%CI (0.48, 10.00), NS) after adjustment for the same covariates. Similar results were obtained from Bootstrap methods except that the odds ratio of LGA infants in rural areas for maternal insurance was significant (95%CI (1.13, 4.37)); urban residence was significantly related with lower odds of birth defect (95%CI (0.23, 0.89)) and congenital heart defect (95%CI (0.19, 0.91)). Conclusions: whether having maternal insurance did have an impact on perinatal outcomes, but the impact of maternal insurance on the perinatal outcomes showed differently between women with urban residence and women with rural residence status. However, it is not clear what are the reason causing the observed differences. Thus, more studies are needed.