Applying Machine Learning Approach to Explore Childhood Circumstances and Self-Rated Health in Old Age-China and the US,2020-2021

Introduction:Childhood circumstances impact senior health,prompting the introduction of machine learning methods to assess their individual and collective contributions to senior health.Methods:Using health and retirement study(HRS)and China Health and Retirement Longitudinal Study(CHARLS),we analyzed 2,434 American and 5,612 Chinese participants aged 60 and above.Conditional inference trees and forests were employed to estimate the influence of childhood circumstances on self-rated health(SRH).Results:The conventional method estimated higher inequality of opportunity(IOP)values in both China(0.039,accounting for 22.67%of the total Gini coefficient 0.172)and the US(0.067,accounting for 35.08%of the total Gini coefficient 0.191).In contrast,the conditional inference tree yielded lower estimates(China:0.022,accounting for 12.79%of 0.172;US:0.044,accounting for 23.04%of 0.191),as did the forest(China:0.035,accounting for 20.35%of 0.172;US:0.054,accounting for 28.27%of 0.191).Childhood health,financial status,and regional differences were key determinants of senior health.The conditional inference forest consistently outperformed others in predictive accuracy,as demonstrated by lower out-of-sample mean squared error(MSE).Discussion:The findings emphasize the need for early-life interventions to promote health equity in aging populations.Machine learning showcases the potential in identifying contributing factors.

Early-Life Circumstances and Cross-Country Disparities in Cognition Among Older Populations — China, the US, and the EU, 2008–2018

What is already known about this topic?Many health challenges have emerged due to rapid population aging,including declined cognitive ability among older adults.What is added by this report?Childhood circumstances have significant and lasting impacts on cognition in old age.This study compared cognition data from China with both the United States(U.S.)and the European Union(EU)during 2008–2018,finding that childhood circumstances could respectively explain 65.4%[95%confidence interval(CI):59.4%,71.4%](China vs.the U.S.)and 38.2%(95%CI:35.1%,41.2%)(China vs.the EU)of the overall differences in cognition among older adults.Family socioeconomic status explained the largest share of differences among all considered childhood circumstances.What are the implications for public health practice?Large disparities in cognition should be addressed by mitigating childhood disadvantages.

On-demand production of hydrogen by reacting porous silicon nanowires with water

On-demand hydrogen generation is desired for fuel cells,energy storage,and clean energy applications.Silicon nanowires(SiNWs)and nanoparticles(SiNPs)have been reported to generate hydrogen by reacting with water,but these processes usually require external assistance,such as light,electricity or catalysts.Herein,we demonstrate that a porous SiNWs array,which is fabricated via the metal-assisted anodic etching(MAAE)method,reacts with water under ambient and dark conditions without any energy inputs.The reaction between the SiNWs and water generates hydrogen at a rate that is about ten times faster than the reported rates of other Si nanostructures.Two possible sources of enhancement are discussed:SiNWs maintain their high specific surface area as they don’t agglomerate,and the intrinsic strain of the nanowires promotes the reactivity.Moreover,the porous SiNWs array is portable,reusable,and environmentally friendly,yielding a promising route to produce hydrogen in a distributed manner.