Health risks associated with long-term ambient temperature and its variability [MRC PHRU]

BACKGROUND

Extreme temperature events are increasing due to climate change. While heat waves and cold snaps are clearly harmful, moderately high and low temperatures may also carry health risk, with some studies showing each degree above or below the optimum temperature associated with 1-2% excess mortality risks. Emerging evidence from case-crossover studies or short-term studies of abrupt changes in ambient temperatures has also suggested that temperature variability likely impacts on health jointly with average temperature levels across different time scale. Long-term prospective studies are needed to reliably assess the long-term health risks associated with variability of ambient temperature.

In the prospective China Kadoorie Biobank (CKB), daily ambient temperature data were collected from each of the 10 geographically diverse areas throughout the study period (2004-2021), along with extensive questionnaire and physical measurements data from all >0.5 million participants. To date, CKB has recorded >70,000 deaths and >1.5 million ICD-10 coded episodes of hospitalisation for >5000 different disease types. Moreover, high-frequency personal and indoor temperature exposure data were also collected in a subset of participants using wearable sensors, together with time-activity diaries and objective physical activity measurements. These data offer a unique opportunity to assess temperature variability and associated health risks at ambient and personal levels. 

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The specific project will be developed according to the candidate’s interests and aptitude, but will likely cover the following objectives:

• To characterise long-term trends and patterns of temperature variability across study sites (e.g. monthly, sub-seasonal, seasonal, inter-annual); 
• To assess the relationships of different timescales of long-term temperature exposure and variability with certain physical traits (e.g. blood pressure, heart rate); 
• To examine the relationships of different timescales of long-term temperature exposure and variability with mortality and morbidity risks of different diseases; 
• To explore the potential effect modification by age, activity, location, and prior health status, etc.

The student will work within a multi-disciplinary team, and will gain training and research experience in systematic literature review, study design and planning, data analysis and scientific writing. By the end of the DPhil, the student will be competent to plan, undertake and interpret analyses of large datasets, and to report research findings, including publications as the lead author in peer-reviewed journals and presentation at national/international conferences.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The project will be based within the CKB group in the Big Data Institute Building. There are excellent facilities and a world-class community of population health and data science researchers. There may be opportunities to work with external partners from other research institutions. 

PROSPECTIVE STUDENT

Candidate will have a good degree in quantitative science subject, with strong interest and background in environmental epidemiology, exposure science or a related discipline. Previous postgraduate training or experience in epidemiology or statistics is necessary.