Search

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) have been associated with earlier natural menopause; however, the underlying mechanisms are not well understood, particularly the extent to which this relationship is mediated by sex hormones. We analyzed data (1999–2017) on 1,120 premenopausal women from the Study of Women's Health Across the Nation (SWAN). Causal mediation analysis was applied to quantify the degree to which follicle-stimulating hormone (FSH) and estradiol levels could mediate the associations between PFAS and incident natural menopause. Participants with higher PFAS concentrations had shorter times to natural menopause, with a relative survival of 0.82 (95% confidence interval (CI): 0.69, 0.96) for linear perfluorooctane sulfonate (n-PFOS), 0.84 (95% CI: 0.69, 1.00) for sum of branched-chain perfluorooctane sulfonate (Sm-PFOS), 0.79 (95% CI: 0.66, 0.93) for linear-chain perfluorooctanoate (n-PFOA), and 0.84 (95% CI: 0.71, 0.97) for perfluorononanoate (PFNA), comparing the highest tertile of PFAS concentrations with the lowest. The proportion of the effect mediated through FSH was 8.5% (95% CI: −11.7, 24.0) for n-PFOS, 13.2% (95% CI: 0.0, 24.5) for Sm-PFOS, 26.9% (95% CI: 15.6, 38.4) for n-PFOA, and 21.7% (6.8, 37.0) for PFNA. No significant mediation by estradiol was observed. The effect of PFAS on natural menopause may be partially explained by variations in FSH concentrations. [ABSTRACT FROM AUTHOR]

Rationale & Objective: Smoking is a modifiable risk factor for various adverse events. However, little is known about the association of smoking with the incidence of acute kidney injury (AKI) in the general population. This study investigated the association of cigarette smoking with the risk of AKI., Study Design: Prospective observational study., Setting & Participants: 14,571 participants (mean age 55±6 years, 55% women, and 25% Black participants) from the ARIC study visit 1 (1987-1989) followed through December 31, 2019., Exposure: Smoking parameters (status, duration, pack-years, intensity, and years since cessation)., Outcome: Incident hospitalization with AKI, defined by a hospital discharge with a diagnostic code relevant to AKI., Analytical Approach: Multivariable Cox regression models., Results: Over a median follow-up period of 26.3 years, 2,984 participants had an incident hospitalization with AKI. Current and former smokers had a significantly higher risk of AKI compared to never smokers after adjusting for potential confounders (HR, 2.22 [95% CI, 2.02-2.45] and 1.12 [1.02-1.23], respectively). A dose-response association was consistently seen for each of smoking duration, pack-years, and intensity with AKI (eg, HR, 1.19 [95% CI, 1.16-1.22] per 10 years of smoking). When years since cessation were considered as a time-varying exposure, the risk of AKI associated with smoking compared with current smokers began to decrease after 10 years, and became similar to never smokers at 30 years (HR for≥30 years, 1.07 [95% CI, 0.97-1.20] vs never smokers)., Limitations: Self-reported smoking measurements and missing outpatient AKI cases., Conclusions: In a community-based cohort, all smoking parameters were robustly associated with the risk of AKI. Smoking cessation was associated with decreased risk of AKI, although the excess risk lasted up to 30 years. Our study supports the importance of preventing smoking initiation and promoting smoking cessation for the risk of AKI., Plain-Language Summary: Smoking is a behavior that is associated with many negative health effects. It is not well understood how smoking relates to the occurrence of acute kidney injury (AKI) in the community. In this study, we looked at data from a group of 14,571 adults who were followed for 26 years to see how different aspects of smoking (such as whether someone smoked, how long they smoked for, how many cigarettes they smoked per day, and whether they quit smoking) were related to AKI. We found that smoking was strongly linked to an increased risk of AKI. This risk decreased after 5-10 years of quitting smoking, but the excess risk lasted up to 30 years. This study shows the importance of preventing people from starting smoking and to encourage smokers to quit to reduce their risk of AKI., (Copyright © 2023 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Background: There is a lack of understanding of how daily step counts differentially affect the risk of all-cause mortality in adult with congestive heart failure (CHF) by sex in the United States (US)., Objectives: To explore the relationship between daily step counts and all-cause mortality in patients with CHF by sex., Methods: This is a cohort analysis from the National Health and Nutrition Examination Survey from 2005 to 2006. Multiple Cox hazard regression was performed to explore the association of step counts and all-cause mortality in patients with CHF by sex., Results: In this study, 363 unweighted samples were enrolled from NHANES 2005-2006, representing about 8.4 million of the US population. Further, 46.28% were women, and the average age was 46 years. Patients with CHF in the more than 5581 steps/day group (HR, 0.31 [95% CI, 0.16-0.58]) had a significantly reduced risk of all-cause mortality compared with the patients in the less 5581 steps/day group after accounting for all covariates. In men, after accounting for all the covariates, there was a significant difference in more than 5581 steps/day group (HR, 0.33 [95% CI, 0.14-0.76]) on all-cause mortality in men with CHF compared with men in the less than 5581 steps/day group., Conclusions: Step count is associated with all-cause mortality in patients with CHF. Taking 5581 daily steps was associated with a decreased risk of all-cause mortality in patients with CHF., Competing Interests: Declaration of Competing Interest This manuscript is the original work of the authors and has not been submitted and is not under consideration for publication elsewhere. All the authors have reviewed the manuscript and approved it before submission. None of the authors has any conflict of interest in the publication of this manuscript. All authors participated in the manuscript preparation and contributed to the conception and design of the study. The specific contributions were as follows: XPC and ZYP was responsible for study conception and design and directed the analyses and writing of the manuscript. GFY, WP, and ND performed the data analyses and drafting of the manuscript. YZ conceived the study and participated in drafting of the manuscript. DSZ and HLZ conceived the study and participated in drafting of the manuscript. YZ carried out the data collection and data analyses and participated in drafting of the manuscript. This manuscript is the original work of the authors and has not been submitted and is not under consideration for publication elsewhere. All the authors have reviewed the manuscript and approved it before submission. None of the authors has any conflict of interest in the publication of this manuscript., (Copyright © 2023. Published by Elsevier Inc.)

Objective: The purpose of this study was to investigate the relationship between bedtime at night and the risk of diabetes in adults., Methods: We extracted data from 14,821 target subjects from the NHANES database for a cross-sectional study. The data on bedtime came from the question in the sleep questionnaire: "What time do you usually fall asleep on weekdays or workdays?". Diabetes was defined as fasting blood sugar ≥ 126mg/dL, or glycohemoglobin ≥ 6.5%, or 2-hour Oral Glucose Tolerance Test blood sugar ≥ 200mg/dL, or taking hypoglycemic agent and insulin, or self-reported diabetes mellitus. A weighted multivariate logistic regression analysis was conducted to explore the relationship between bedtime at night and diabetes in adults., Results: From 19:00 to 23:00, a significantly negative association can be found between bedtime and diabetes(OR, 0.91 [95%CI, 0.83, 0.99]). From 23:00 to 02:00, The relationship between the two was positive(OR, 1.07 [95%CI, 0.94, 1.22]), nevertheless, the P values was not statistically significant(p = 0.3524). In subgroup analysis, from 19:00-23:00, the relationship was negative across genders, and in males, the P-values were still statistically significant(p = 0.0414). From 23:00-02:00, the relationship was positive across genders., Conclusion: Earlier bedtime (before 23:00) increased the risk of developing diabetes. And this effect was not significantly different between male and female. For bedtime between 23:00-2:00, there was a trend of increasing the risk of diabetes as the bedtime was delayed., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ouyang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)