Incarcerated African American men who use marijuana are vulnerable to polysubstance use, which is associated with greater risk for negative health and psychosocial outcomes than marijuana use alone. It is imperative to understand risk and protective factors for polysubstance use among this vulnerable population to inform the development of culturally tailored substance use interventions. The current study examined the association between John Henryism Active Coping (JHAC), family social support, psychiatric symptoms, and polysubstance use among African American incarcerated men who frequently use marijuana. Results indicated that higher John Henryism Active Coping (JHAC) is associated with decreased likelihood of engaging in polysubstance use, while psychiatric symptoms are associated with increased likelihood of polysubstance use. Incorporating elements of JHAC into concurrent mental health and substance use treatment may reduce risk for overdose and reincarceration among African American incarcerated men upon release into the community.
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http://dx.doi.org/10.1080/15332640.2020.1793861 | DOI Listing |
J Racial Ethn Health Disparities
January 2025
Epidemiology and Health Economics Research (EHER), Universidad Científica del Sur, Lima, Peru.
Background: The Afro-Peruvian population is one of the ethnic minorities most affected by cultural, socioeconomic, and health barriers; however, there is little evidence on health inequalities in this ethnic group. Therefore, We aimed to determine health inequalities among the Peruvian Afro-descendant population in comparison with non-Afro-descendants.
Methods: A cross-sectional study was conducted using data from the Demographic and Family Health Survey 2022.
Alzheimers Dement
December 2024
Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Background: Several viruses have been linked to Alzheimer disease (AD) by independent lines of evidence.
Method: Whole genome and whole exome sequences (WGS/WES) derived from brain (3,404 AD cases, 894 controls) and blood (15,612 AD cases, 24,544 controls) obtained from European ancestry (EU), African American (AA), Mexican (HMX), South Asian Indian (IND), and Caribbean Hispanic (CH) participants of the Alzheimer's Disease Sequencing Project (ADSP) and 276 AD cases 3,584 controls (all EU) from the Framingham Heart Study (FHS) that did not align to the human reference genome were aligned to viral reference genomes. A genome-wide association study (GWAS) for viral DNA load was conducted using PLINK software and regression models with covariates for sex, age, ancestry principal components, and tissue source.
Alzheimers Dement
December 2024
Boston University Alzheimer's Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Background: Alzheimer's disease (AD) has both genetic and environmental risk factors. Gene-environment interaction may help explain some missing heritability. There is strong evidence for cigarette smoking as a risk factor for AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of California, Davis School of Medicine, Sacramento, CA, USA.
Background: Examining the neuropathology of the oldest-old has significantly advanced our understanding of the multiple etiologies in very late life. Most studies have included exclusively White decedents with limited ethnoracial diversity. Our goal was to characterize neuropathology in a cohort of ethnically and racially diverse oldest-old decedents.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA.
Background: Although high-throughput DNA/RNA sequencing technologies have generated massive genetic and genomic data in human disease, translation of these findings into new patient treatment has not materialized by lack of effective approaches, such as Artificial Intelligence (AL) and Machine Learning (ML) tools.
Method: To address this problem, we have used AI/ML approaches, Mendelian randomization (MR), and large patient's genetic and functional genomic data to evaluate druggable targets using Alzheimer's disease (AD) as a prototypical example. We utilized the genomic instruments from 9 expression quantitative trait loci (eQTL) and 3 protein quantitative trait loci (pQTL) datasets across five human brain regions from three biobanks.
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