Association between circadian physical activity patterns and cancer incidence through regulation of inflammation: A UK biobank study.

BACKGROUND: Physical activity (PA) has been linked with cancer incidence. However, the effects and mechanisms underpinning circadian PA trajectories on cancer remain elusive. This study aimed to explore the optimal PA patterns in reducing cancer incidence and the associated potential mediators. METHODS: Between 2006 and 2010, 502,400 participants were recruited from the UK Biobank. Out of these, 102,323 participants wore accelerometers, which allowed for collecting acceleration data continuously over 7 days. After excluding participants with previous cancer history, 96,687 participants were included in K-means cluster analysis to identify PA trajectories. The association between PA and cancer incidence was assessed using Cox regression analysis. Additionally, we investigated the mediating role of inflammation. RESULTS: A total of 5995 cancer cases were recorded during a median follow-up of 7.1 years. Four distinct PA trajectories (persistent low, single peak, double peak, and vigorous) were identified. The ideal PA patterns reduced the risk of 7 out of 17 site-specific cancers, with the lowest hazard ratios and 95% confidence intervals of cancer for bladder (0.59, 0.40-0.86), breast (0.73, 0.60-0.89), kidney (0.45, 0.26-0.78), lung (0.59, 0.41-0.84), myeloma (0.49, 0.27-0.88), and oral & pharynx (0.51, 0.26-0.98) in the vigorous pattern and for colorectal (0.71, 0.54-0.93) in the double peak pattern. Moreover, the mediating effects of inflammation were significant. CONCLUSION: Optimal PA trajectories reduced cancer incidence, especially in double peak and vigorous patterns. The protective effect was associated with both intensity and circadian rhythm. Crucially, this protection was mediated by inflammation regulation.

Association between the trajectory of ideal cardiovascular health metrics and incident chronic kidney disease among 27,635 older adults in northern China-a prospective cohort study.

BACKGROUND: There is a lack of relevant studies evaluating the long-term impact of cardiovascular health factor (CVH) metrics on chronic kidney disease (CKD). OBJECTIVE: This study investigates the long-term change in CVH metrics in older people and explores the relationship between CVH metrics trajectory and CKD. METHODS: In total, 27,635 older people aged over 60 from the community-based Tianjin Chronic Kidney Disease Cohort study were enrolled. The participants completed five annual physical examinations between January 01, 2014, and December 31, 2018, and a subsequent follow-up between January 01, 2019, and December 31, 2021. CVH metrics trajectories were established by the group-based trajectory model to predict CKD risk. The relationships between baseline CVH, CVH change (ΔCVH), and CKD risk were also explored by logistic regression and restricted cubic spline regression model. In addition, likelihood ratio tests were used to compare the goodness of fit of the different models. RESULTS: Six distinct CVH metrics trajectories were identified among the participants: low-stable (11.19%), low-medium-stable (30.58%), medium-stable (30.54%), medium-high-decreased (5.46%), medium-high-stable (18.93%), and high-stable (3.25%). After adjustment for potential confounders, higher CVH metrics trajectory was associated with decreased risk of CKD (P for trend < 0.001). Comparing the high-stable with the low-stable group, the risk of CKD decreased by 46%. All sensitivity analyses, including adjusting for baseline CVH and removing each CVH component from the total CVH, produced consistent results. Furthermore, the likelihood ratio test revealed that the model established by the CVH trajectory fit better than the baseline CVH and Δ CVH. CONCLUSION: The higher CVH metrics trajectory and improvement of CVH metrics were associated with decreased risk of CKD. This study emphasized the importance of improving CVH to achieve primary prevention of CKD in older people.

Fibrinogen/Albumin ratio: A more powerful prognostic index for patients with end-stage renal disease.

BACKGROUND: Microinflammation is linked to an increased risk of death due to cardiovascular disease (CVD) in patients with end-stage renal disease (ESRD). Although the fibrinogen/albumin ratio (FAR), a novel inflammatory marker, has been shown to predict mortality in various diseases, limited evidence is available for its role in ESRD. The purpose of this study is to explore the prognostic value of the FAR in ESRD patients on peritoneal dialysis (PD). METHODS: In this retrospective observational study, we enrolled patients with ESRD who underwent PD therapy in our hospital between 1 January 2011 and 31 December 2017. The Kaplan-Meier method and Cox proportional hazards models were used to determine the contact between the FAR level and mortality. RESULTS: A total of 562 patients were enrolled in our research. The median FAR was 0.12, and patients were divided into two groups (low FAR group: FAR < 0.12, n = 250, and high FAR group: FAR ≥ 0.12, n = 312) according to the median FAR. Kaplan-Meier curves showed that the cumulative incidences of both all-cause mortality and CVD mortality were significantly higher in patients with FAR ≥ 0.12 (both P < .001). In multivariable analysis, the high FAR group had an important increased risk of all-cause and CVD mortality (HR: 1.80; 95% CI: 1.03-3.14, P = .038 and HR: 2.31; 95% CI: 1.17-4.59, P = .016, respectively). CONCLUSIONS: Our results suggest that a high baseline FAR value is an independent prognostic factor in ESRD patients on PD.

Knowledge of blood sugar control standard brings the higher attainment rate of HbA1c.

OBJECTIVE: To analyze the important controllable factors which affect the glycemic control of diabetes. METHODS: A cross-sectional study was carried out to examine the role of relevant characteristics in glycemic control by a sampling investigation of 430 diabetic patients in Hunan, China. A questionnaire was designed for personal interviews to collect data. Univariate regression analysis and multiple linear regression analysis were used to evaluate the effects of various factors on glycated hemoglobin A1c (HbA1c) control. RESULTS: The level of HbA1c in 430 patients was (8.7±2.6)%, and the value in 34% patients among them was ≤ 7.0%. Base on univariate regression analysis some factors were associated with good HbA1c control, including age, diabetic education, self monitoring of blood glucose, knowledge of blood sugar control standard, living environment, and self-owned glucometer. However, the upgraded treatment was associated with poor control. Based on multiple linear regression analysis, the first four factors mentioned above were protective factors for HbA1c while upgraded treatment was risk factor for HbA1c. CONCLUSION: Knowledge of blood sugar control standard, diabetic education and self monitoring of blood glucose are important controllable factors for better glycemic control of diabetes.