Preventative problem-solving and clear communication: Reflections on environmental health data collection in northern China
Talia Sternbach, MSc in Epidemiology Candidate
This winter I spent three-and-a-half months in northern China conducting field work to inform both my master’s thesis and a broader environmental health policy evaluation project. With prior global health experience limited to smaller engagements through personal travel and prior coursework, I was excited to support a large, interdisciplinary project that seamlessly combines my background in environmental health and urban studies with ongoing training in epidemiology and interest in global health policy.
The Beijing Household Energy Transitions study is a policy evaluation of a clean energy transition program recently implemented in the peri-urban regions of Beijing, China. It aims to evaluate the effect of simultaneous coal ban and clean energy subsidy policies on air pollution, indoor temperature, and cardiovascular and respiratory health over three years. My research specifically investigates the relationship of temperature with cardiovascular health. Data collection involved visiting more than 1,000 households in fifty villages, administering detailed questionnaires, conducting health assessments, and deploying hundreds of air pollution monitors and temperature sensors. I joined our field staff and project leads, learning the preparation, adaptation, and communication needed to collect high-quality environmental and health data in a global health context.
The central goal of our field work was to compile a “perfect” dataset – one that is free from biases, has accurate values and complete observations for each household, and makes analysis easy and statistical inference convincing. Though a seemingly straightforward task, it is easy to imagine how a monthly income of ¥2,000 could be accidentally recorded as ¥200 or that the charging cable for the air pollution monitor might be just short of the outlet in the participant’s home. Both instances would result in faulty or missing datapoints. Overcoming these challenges and others largely rested with our capacity to anticipate potential problems and adapt to the situation in real time. We arrived in each village armed with extension cords and checked incoming surveys from the back of our minivan for odd responses. In the weeks leading up to data collection we also dedicated significant time to field staff training and calibrating air pollution monitors (a process used to ensure the validity of air quality measurements). These preventative problem-solving activities laid a foundation for accurate measurement of key environmental exposures and empowered field staff (myself included) to respond to a range of conceivable situations.
About the author
Talia Sternbach is a second year master’s student in Epidemiology and graduate intern at the Institute for Health and Social Policy. She received her B.A. in Environmental Science, concentrating in environmental health and urban systems. She recently returned from China where she was collecting data towards her master’s thesis, investigating the health impacts of indoor temperature, and a broader environmental health policy evaluation. Talia was a 2019 Global Health Scholar and is a current Mitacs Globalink International Research Award holder.