H3Africa AWI-Gen Collaborative Centre: a resource to study the interplay between genomic and environmental risk factors for cardiometabolic diseases in four sub-Saharan African countries.

Africa is experiencing a rapid increase in adult obesity and associated cardiometabolic diseases (CMDs). The H3Africa AWI-Gen Collaborative Centre was established to examine genomic and environmental factors that influence body composition, body fat distribution and CMD risk, with the aim to provide insights towards effective treatment and intervention strategies. It provides a research platform of over 10 500 participants, 40-60 years old, from Burkina Faso, Ghana, Kenya and South Africa. Following a process that involved community engagement, training of project staff and participant informed consent, participants were administered detailed questionnaires, anthropometric measurements were taken and biospecimens collected. This generated a wealth of demographic, health history, environmental, behavioural and biomarker data. The H3Africa SNP array will be used for genome-wide association studies. AWI-Gen is building capacity to perform large epidemiological, genomic and epigenomic studies across several African counties and strives to become a valuable resource for research collaborations in Africa.

Spatial variations in childhood mortalities at the Dodowa Health and Demographic Surveillance System site of the INDEPTH Network in Ghana.

OBJECTIVE: To determine the distribution of under-five deaths in Dodowa Health and Demographic Surveillance Area (DHDSA) and to identify possible clustering of deaths. METHODS: Data from the Dodowa Health and Demographic Surveillance System (DHDSS) were used for the analysis. These data covered a population of about 89 371 in 371 communities in seven area councils from 2005-2006. Under-five crude mortality rates were calculated for each community and area council. The central feature command in ArcGIS 9.2 was used to locate the centroid of each community from a shapefile of housing structures of communities. A spatial scan statistic was used to identify and test for clusters of under-five deaths. Data on socioeconomic indicators and insecticide treated net (ITN) ownership were analysed to determine the status of the clustered communities. RESULTS: Although several clusters of high under-five mortality were identified, only two were significant in two area councils: one cluster comprising three communities and another involving one community. Analysis of probable risk factors indicates that the single community which formed a significant cluster in Osuwem area council was seriously disadvantaged. About 71% of its households were in the poorest quintile, no household had ITN, electricity connection, good source of water or health insurance. The three communities that formed the significant cluster in Ningo area council, however, fared well in almost all indicators. CONCLUSION: The identified significant clustering of under-five mortality demands further studies to investigate the causes of the clustering, especially the Ningo area council.

Mortality patterns, 1993-98, in a rural area of Burkina Faso, West Africa, based on the Nouna demographic surveillance system.

The Nouna demographic surveillance system database was analysed for the period 1993-98. Basic demographic parameters, age-specific and age-standardized mortality rates were calculated and a seasonal variation in mortality was analysed. Poisson regression was used to model the calculated mortality rates and to investigate the seasonal mortality pattern. Both the population distribution by age and the mortality rates reflect a typical pattern of population structures and total mortality in rural Africa as a whole: high childhood mortality and a young population (about 60% are up to age 25; about 10% above age 64). We identified a significant seasonal pattern with highest mortality rates in February. Demographic surveillance systems in Africa provide a viable method for the collection of reliable data on vital events in rural Africa and should therefore be established and supported.

Clustering of childhood mortality in rural Burkina Faso.

BACKGROUND: Childhood mortality is a major public health problem in sub-Saharan Africa. For the implementation of efficient public health systems, knowledge of the spatial distribution of mortality is required. METHODS: Data from a demographic surveillance research project were analysed which comprised information obtained for about 30 000 individuals from 39 villages in northwest Burkina Faso (West Africa) in the period 1993--1998. Total childhood mortality rates were calculated and the geographical distribution of total childhood mortality was investigated. In addition, data from a cohort of 686 children sampled from 16/39 of the villages followed up during a randomized controlled trial in 1999 were also used to validate the results from the surveillance data. A spatial scan statistic was used to test for clusters of total childhood mortality in both space and time. RESULTS: Several statistically significant clusters of higher childhood mortality rates comprising different sets of villages were identified; one specific village was consistently identified in both study populations indicating non-random distribution of childhood mortality. Potential risk factors which were available in the database (ethnicity, religion, distance to nearest health centre) did not explain the spatial pattern. CONCLUSION: The findings indicate non-random clustering of total childhood mortality in the study area. The study may be regarded as a first step in prioritizing areas for follow-up public health efforts.