Alex Ayenew Chereka, Addisalem Workie Demsash, Fikadu Wake Butta, Adamu Ambachew Shibabaw, Chernet Desalegn Gebeyehu, Daniel Adane, Wubalem Dilie Limeneh, Amare Dagnew Fentahun, Mathias Nega Tadesse, Gemeda Wakgari Kitil
Examining students' level of understanding toward COVID-19 and its associated factors in Ethiopia: a systematic review and meta-analysis
Frontiers in public health
structural racism produces mental health disparities studies examined impact individual factors poverty education collective contribution elements manifestations structural racism less explored milwaukee county wisconsin racial socioeconomic diversity provides unique context multifactorial investigation research aimed delineate association structural racism mental health disparities milwaukee county using combination geospatial deep learning techniques used secondary data sets data aggregated anonymized released federal agencies compiled 217 georeferenced explanatory variables across domains initially deliberately excluding racebased factors focus nonracial determinants approach designed reveal underlying patterns risk factors contributing poor mental health subsequently reintegrating race assess effects racism quantitatively variable selection combined treebased methods random forest conventional techniques supported variance inflation factor pearson correlation analysis multicollinearity mitigation geographically weighted random forest model used investigate spatial heterogeneity dependence selforganizing maps combined kmeans clustering used analyze data milwaukee communities focusing quantifying impact structural racism prevalence poor mental health 12 influential factors collectively accounted 9511 variability mental health across communities top 6 factorssmoking poverty insufficient sleep lack health insurance employment agewere particularly impactful predominantly african american neighborhoods disproportionately affected 223 times likely encounter highrisk clusters poor mental health findings demonstrate structural racism shapes mental health disparities black community members disproportionately impacted multifaceted methodological approach underscores value integrating geospatial analysis deep learning understand complex social determinants mental health insights highlight need targeted interventions addressing individual systemic factors mitigate mental health disparities rooted structural racism