Biomarkers.

Background: The burden of Alzheimer's disease and related dementias is growing fast in Africa. The Recruitment and Retention for Alzheimer's Disease Diversity Genetic Cohorts in the Alzheimer's Disease Sequencing Project (READD-ADSP) has commenced recruitment of 5000 African participants (AD and cognitively unimpaired individuals) to generate genomic and biomarker data to better characterize AD genetic architecture in Africa. Participating countries, part of the African Dementia Consortium (AfDC) include Nigeria, Ghana, Benin, Cameroon, Uganda, Kenya, Ethiopia, Tanzania, and Mozambique.

Public Health.

Background: Understanding the genetic underpinnings of Alzheimer's disease is crucial for advancing research and developing targeted interventions. Genomic research in dementia in Africa is of utmost importance based on recent reports from studies in African Americans that African ancestral gene is associated with lower risk effect for developing AD. However, dementia related genetic study is an evolving research in sub-Saharan Africa with peculiar challenges influencing participant recruitment.

Dementia Care Research and Psychosocial Factors.

Background: Majority of people living worldwide live in low- and middle- income countries, including sub-Saharan Africa (SSA). Most cognitive assessment batteries for Alzheimer's Disease(AD), are developed in high income countries (HICs), where most international dementia collaborations and data originate. The African Dementia Consortium (AfDC) is a new scientific collaboration network currently participating in the Recruitment and Retention for Alzheimer's Disease Diversity Genetic Cohorts in the Alzheimer's Disease Sequencing Project (READD-ADSP).

Risk Assessment Score and Chi-Square Automatic Interaction Detection Algorithm for Hypertension Among Africans: Models From the SIREN Study.

Background: This study aimed to develop a risk-scoring model for hypertension among Africans.

Methods: In this study, 4413 stroke-free controls were used to develop the risk-scoring model for hypertension. Logistic regression models were applied to 13 risk factors.