Association of circulation very long chain saturated fatty acids with depression in NHANES 2011-2014.

BACKGROUND: Recent studies have shown that elevated levels of medium and long chain saturated fatty acids are associated with an increased risk of depression. However, little is known about the effect of very long chain saturated fatty acids (VLSFAs) on depression. Therefore, our study aimed to examine the association between VLSFAs and depression in the US adult population. METHODS: A total of 2706 participants with serum VLSFAs detection from NHANES 2011-2014 were included in the study. Logistic regression models were used to evaluate the association between quartile levels of serum VLSFAs (20:0, 22:0, 23:0, 24:0, and total VLSFA) and depression. RESULTS: After adjusting for multiple variables, we found that increased circulating levels of 22:0, 23:0, 24:0 and total VLSFA were linearly associated with a reduced risk of depression (model 3, Q4 OR: 0.658, 95 % CI: 0.438-0.989, P-trend = 0.023; OR: 0.515, 95 % CI: 0.339-0.782, P-trend<0.001; OR: 0.556, 95 % CI: 0.370-0.835, P-trend = 0.003; OR: 0.652, 95 % CI: 0.435-0.976, P-trend = 0.021, respectively). Additionally, individuals with the highest serum ratios of 22:0/16:0, 23:0/16:0, 24:0/16:0 and total VLSFA/16:0 also had a lower risk of depression after adjusting for multiple variables compared to the group with the lowest serum VLSFAs/16:0 (P-trend = 0.001, <0.001, 0.001 and 0.004, respectively). Moreover, the decreasing trend of depression associated with increased VLSFAs/18:0 remained significant. CONCLUSION: In conclusion, our findings suggest that increased circulating levels of 22:0, 23:0, 24:0 and total VLSFA may have a protective effect against the risk of depression.

The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003-2018.

BACKGROUND: In the American population, the relationship between the triglyceride-glucose (TyG) index and TYG combined with indicators of obesity and cardiovascular disease (CVD) and its mortality has been less well studied. METHODS: This cross-sectional study included 11,937 adults from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Cox proportional hazards model, binary logistic regression analyses, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were used to analyze the relationship between TyG and its combined obesity-related indicators and CVD and its mortality. Mediation analysis explored the mediating role of glycated hemoglobin and insulin in the above relationships. RESULTS: In this study, except for no significant association between TyG and CVD mortality, TyG, TyG-WC, TyG-WHtR, and TyG-BMI were significantly and positively associated with CVD and CVD mortality. TyG-WHtR is the strongest predictor of CVD mortality (HR 1.66, 95% CI 1.21-2.29). The TyG index correlated better with the risk of coronary heart disease (OR 2.52, 95% CI 1.66-3.83). TyG-WC correlated best with total CVD (OR 2.37, 95% CI 1.77-3.17), congestive heart failure (OR 2.14, 95% CI 1.31-3.51), and angina pectoris (OR 2.38, 95% CI 1.43-3.97). TyG-WHtR correlated best with myocardial infarction (OR 2.24, 95% CI 1.45-3.44). RCS analyses showed that most of the above relationships were linear (P-overall < 0.0001, P-nonlinear > 0.05). Otherwise, ROC curves showed that TyG-WHtR and TyG-WC had more robust diagnostic efficacy than TyG. In mediation analyses, glycated hemoglobin mediated in all the above relationships and insulin-mediated in partial relationships. CONCLUSIONS: TyG-WC and TyG-WtHR enhance CVD mortality prediction, diagnostic efficacy of CVD and its mortality, and correlation with some CVD over and above the current hottest TyG. TyG-WC and TyG-WtHR are expected to become more effective metrics for identifying populations at early risk of cardiovascular disease and improve risk stratification.

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank.

BACKGROUND: To explore the relationship between sleep patterns and cardiovascular disease (CVD) incidence and mortality risk in a population with type 2 diabetes through a UK Biobank sample. METHODS: A total of 6860 patients with type 2 diabetes were included in this study. Five sleep factors (including Chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) were collected as a questionnaire. The calculation generates a sleep score of 0-5, and then three sleep patterns were defined based on the sleep scores: poor sleep pattern (0-2), Intermediate sleep pattern (3-4), and healthy sleep pattern (5). HRs and 95% confidence intervals were calculated by multivariate COX proportional risk model adjustment. Restricted cubic splines were used to validate linear associations between sleep scores CVD events. RESULTS: Our results found a reduced risk of CVD events in individuals with healthy sleep patterns compared to participants with poor sleep patterns. CVD Mortality (HR, 0.690; 95% CI 0.519-0.916), ASCVD (Atherosclerosis CVD) (HR, 0.784; 95% CI 0.671-0.915), CAD (Coronary Artery Disease) (HR, 0.737; 95% CI 0.618-0.879), PAD (Peripheral Arterial Disease) (HR, 0.612; 95% CI 0.418-0.896), Heart Failure (HR, 0.653; 95% CI 0.488-0.875). Restricted cubic spline responded to a negative linear correlation between sleep scores and CVD Mortality, ASCVD, CAD, PAD, and Heart Failure. CONCLUSIONS: Healthy sleep patterns are significantly associated with a reduced risk of CVD Mortality, ASCVD, CAD, PAD, and Heart Failure in the diabetes population.