Researchers study effects of secondhand smoke on children
About a third of the world’s smokers live in China according to the World Health Organization, and an estimated 1 million Chinese die each year fromtobacco-related illnesses. The high prevalence male smokers in China suggest that a large number ofyoung children are exposed to secondhand smokeat home. This is especially true in rural areas due to the lack of tobacco control policy initiative in those areas and the high prevalence of smoking among people residing in rural areas. GHRC Prof Abu Abdullah is leading a project to minimize the adverse health effects of secondhand smoking on children, especially in rural China.
Working with colleagues at Fudan University Taizhou Centers for Disease Control & Prevention and Kunming Medical University, Abdullah and GHRC team members will gather baseline data on secondhand smoke exposure among young childrerin the rural areas of Taizhou City (Zhejiang province and Dali city (Yunnan province). They will then test the effectiveness of an intervention in which community health workers will counsel parents about the importance of not smoking around their infants and children, and will offer assistance in stopping smoking.
Rural TB Study examines health services use
In August 2016, the GHRC’s Dr. Di Dongwas awarded the National Natural Science Foundation of China (NSFC) Young Scientist Fund to research rural tuberculosis (TB) patients’ access to hospital care as well as the cost of care, and the financial burden to patients and families.
There are more than 5 million TB patients in China and there are major challenges to the control of TB in China. Those challenges include sub-optimal treatment adherence, drug-resistant TB, and inappropriate treatment (such as a high rate of hospital admissions).
Dr. Dong, together with Prof. ShenglanTang, and research associates Weixi Jiang and Shu Chen, will consolidate large sets of TB data in three provinces.
The study, Di said, will also explore the best technical strategy for linking different databases, and the feasibility of using big data in disease management and policy evaluation.
