Death rates at specific life stages mold the sex gap in life expectancy

Why do women live longer than men? Here, we mine rich lodes of demographic data to reveal that lower female mortality at particular ages is decisive—and that the important ages changed around 1950. Earlier, excess mortality among baby boys was crucial; afterward, the gap largely resulted from elevated mortality among men 60+. Young males bear modest responsibility for the sex gap in life expectancy: Depending on the country and time, their mortality accounts for less than a quarter and often less than a 10th of the gap. Understanding the impact on life expectancy of differences between male and female risks of death by age, over time, and across populations yields insights for research on how the lives of men and women differ.

Between ages 15 and 40, death rates for men are usually two or three times higher than death rates for women. This disparity has fueled widespread interest in the ratio of male to female death rates over the life course and in why it is exceptionally high for younger adults (1–6). Between ages 15 and 40, however, numbers of deaths are relatively low, so the high ratio of male to female death rates has a modest impact on the gap between female and male life expectancies. The sex difference in life expectancy hinges on differences in mortality risks at the ages when deaths are relatively common (7). Up through the early decades of the 20th century, these ages were at both extremes of life, infancy and old age. Afterward, death mostly struck after age 60. Here, we investigate variation across populations, over time, and over the life course in absolute and relative differences in mortality for men and women. We discuss what insights can be gained by scrutinizing relative risks compared to what can be learned by analyzing absolute risks.     

Cardiac Surgery in Patients With Liver Cirrhosis (CASTER) Study: Early and Long-Term Outcomes

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Empagliflozin restores chronic kidney disease–induced impairment of endothelial regulation of cardiomyocyte relaxation and contraction

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A National Analysis of Minimally Invasive Vs Open Segmentectomy for Stage IA Non–Small-Cell Lung Cancer

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Improving HIV medical care engagement by attending to status disclosure and social support

ABSTRACT

Expeditious linkage and consistent engagement in medical care is important for people with HIV’s (PWH) health. One theory on fostering linkage and engagement involves HIV status disclosure to mobilize social support. To assess disclosure and social support’s association with linkage and engagement, we conducted a qualitative study sampling black and Latino men who have sex with men (MSM of color) in the U.S. Participants' narratives presented mixed results. For instance, several participants who reported delaying, inconsistent access, or detachment from care also reported disclosing for support purposes, yet sporadic engagement suggests that their disclosure or any subsequent social support have not assisted. The findings contribute to the literature that questions disclosure and social support’s influence on care engagement, especially when decontextualized from circumstances and intentions. Our findings suggest the mechanics of disclosure and social support require planned implementation if intending to affect outcomes, especially among MSM of color. From the findings, we explore steps that may bolster interventions seeking to anchor medical care engagement.     

Circadian Rhythmicity as a Predictor of Quality of Life in Allogeneic Hematopoietic Cell Transplant Patients

Context

Quality of life (QoL) is increasingly recognized as an important outcome of cancer treatment. Previous studies have examined clinical predictors of QoL, but with the increasing prevalence of wearable sensors that monitor sleep and activity patterns, further investigation into whether these behaviors are predictive of post-treatment QoL is now feasible. Among patients receiving aggressive cancer treatment such as hematopoietic cell transplantation (HCT), analysis of circadian rhythms (24-hour patterns of sleep and activity) via wearable sensors is limited.