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The Kalyani cohort created in 2010 by the National Institute of Biomedical Genomics, West Bengal, India, is designed to serve as a platform for conducting prospective basic and translational studies on epidemiology and genomics of health and disease-related parameters, particularly of non-communicable diseases (NCDs). The overall goal is to assess behavioural, biological, genetic, social and environmental factors and obtain necessary evidence for effective health improvement. Collected baseline data comprise 15727 individuals, >14 years of age from seven municipal wards in the Kalyani and Gayeshpur regions. Data are being collected on demographics, current health status, medical history and health-related behaviours. Blood samples were also collected from a subset of individuals (n = 5132) and analysed for estimation of known markers of NCDs. DNA has been extracted from blood samples and stored for future use. Important baseline findings include a high prevalence of diabetes, dyslipidemias and hypothyroidism. Prevalence estimates for these disorders obtained from self-reported data are significantly lower, indicating that participants are unaware of their health problems. The identification of ‘at risk’ individuals will allow formation of sub-cohorts for further investigations of epidemiological and genetic risk factors for NCDs. Access to the resource, including data and blood samples, created by this study will be provided to other researchers.
Malaria elimination is on global agendas following successful transmission reductions. Nevertheless moving from low to zero transmission is challenging. South Africa has an elimination target of 2018, which may or may not be realised in its hypoendemic areas.
Methods
The Agincourt Health and Demographic Surveillance System has monitored population health in north-eastern South Africa since 1992. Malaria deaths were analysed against individual factors, socioeconomic status, labour migration and weather over a 21-year period, eliciting trends over time and associations with covariates.
Results
Of 13 251 registered deaths over 1.58 million person-years, 1.2% were attributed to malaria. Malaria mortality rates increased from 1992 to 2013, while mean daily maximum temperature rose by 1.5 °C. Travel to endemic Mozambique became easier, and malaria mortality increased in higher socioeconomic groups. Overall, malaria mortality was significantly associated with age, socioeconomic status, labour migration and employment, yearly rainfall and higher rainfall/temperature shortly before death.
Conclusions
Malaria persists as a small but important cause of death in this semi-rural South African population. Detailed longitudinal population data were crucial for these analyses. The findings highlight practical political, socioeconomic and environmental difficulties that may also be encountered elsewhere in moving from low-transmission scenarios to malaria elimination.
The coverage of health insurance as measured by enrollment rates has increased significantly in Vietnam. However, maintaining health insurance to the some groups such as the farmer, the borderline poor and informal workers, etc. has been very challenging. This paper examines the situation of health insurance drop-out among the adult population in sub-rural areas of Northern Vietnam from 2006 to 2013, and analyzes several socio-economic correlates of the health insurance drop-out situation. Data used in this paper were obtained from Health and Demographic Surveillance System located in Chi Linh district, an urbanizing area, in a northern province of Vietnam. Descriptive analyses were used to describe the level and distribution of the health insurance drop-out status. Multiple logistic regressions were used to assess associations between the health insurance drop-out status and the independent variables. A total of 32 561 adults were investigated. We found that the cumulative percentage of health insurance drop-out among the study participants was 21.2%. Health insurance drop-out rates were higher among younger age groups, people with lower education, and those who worked as small trader and other informal jobs, and belonged to the non-poor households. Given the findings, further attention toward health insurance among these special populations is needed.
