Close

Acclimatization to Urban Heat Island effect on heat- and cold-related mortality in cities in Japan and England

Title of PhD project / theme

Acclimatization to Urban Heat Island effect on heat- and cold-related mortality in cities in Japan and England

Supervisory team

Dr Ai Milojevic (Lead, Assistant Professor, LSHTM / PHP) Ai.Milojevic@lshtm.ac.uk

Professor Masahiro Hashizume (Nagasaki University, University of Tokyo) hashizume@m.u-tokyo.ac.jp

Dr Chris Fook Sheng Ng (Nagasaki University) chrisng@nagasaki-u.ac.jp

Brief description of project / theme

It is well-known that heat mortality risk is increased in neighbourhoods subject to the urban heat island (UHI), but little attempts were reported to identify degrees of difference in susceptibility to heat and cold between cool and hot areas (i.e. acclimatization to UHI) with notable exceptions.1-3 In this PhD project, we will examine and quantify the degree of acclimatization to heat- and cold-related mortality in relation to UHI anomalies in the selected Japanese and English cities. We will apply the novel methods developed by the supervisory team2 utilizing legacy of five decades’ (1972-2020) individual mortality records with city-level geographical markers in Japan and those of 2.5 decades (1993-2019) with finer geographical markers (Lower Super Output Area level) in England. UHI anomalies will be defined by historical monitoring records for each city and surrounded area in Japan and weather unified model combined with safelight data across the cities in England. Our primary focus for the Japanese case cities will be the changes in degree of acclimatization over five decades. With the English cities, UHI anomalies will be identified with the use of cutting-edge urban heat model using relatively recent finer spatial resolution data.

Main objectives of this research include:

  1. To determine whether hotter neighbourhoods (those affected by a UHI) have higher excess mortality on hot days or lower mortality on cold days in selected case cities in Japan and England, allowing for adjustment of other factors;
  2. To estimate the extent to which such differences are consistent with expectations given how much hotter or colder those areas are compared with the target city overall;
  3. To examine how did degree of acclimatization to UHI change over five decades in Japanese cities; and
  4. To develop the methods to estimate heat- and cold-related mortality accounting for possible (empirically observed) acclimatization in urban cities.

Cities in Japan (Tokyo, Osaka, Nagoya, Kyoto, Fukuoka, Sapporo) have been experiencing significant UHI phenomenon over the twentieth century. The mean temperature in these large cities has risen by 2-3°C, while the globally averaged temperature risen by 0.6°C. To understand its health impacts and possible acclimatization (if any) is the current highest priorities for the government so that they can develop practical and effective mitigation strategies. This project will provide empirical knowledge base of health impacts of UHI and public acclimatization that need to be accounted for new policies to mitigate UHI impacts.

References:

1. Chung Y, Yang D, Gasparrini A, et al. Changing Susceptibility to Non-Optimum Temperatures in Japan, 1972-2012: The Role of Climate, Demographic, and Socioeconomic Factors. Environ Health Perspect 2018;126(5):057002. doi: 10.1289/ehp2546 [published Online First: 2018/05/05]

2. Milojevic A, Armstrong BG, Gasparrini A, et al. Methods to Estimate Acclimatization to Urban Heat Island Effects on Heat- and Cold-Related Mortality. Environ Health Perspect 2016;124(7):1016-22. doi: 10.1289/ehp.1510109 [published Online First: 2016/02/10]

3. Ng CFS, Boeckmann M, Ueda K, et al. Heat-related mortality: Effect modification and adaptation in Japan from 1972 to 2010. Global Environmental Change 2016;39:234-43. doi: https://doi.org/10.1016/j.gloenvcha.2016.05.006

The role of LSHTM and NU in this collaborative project

The existing Nagasaki University (NU) – LSHTM collaboration in PHP, specifically on Environmental Health Research in South East Asia will lay the foundation to the project. Additional support and transdisciplinary resources are accessible at the Centre on Climate Change and Planetary Health at LSHTM. Wellcome Trust-funded HEROIC (Health and Economic impacts of Reducing Overheating in Cities) project will provide additional support for UHI modelling for English cities. The new collaboration is planned with Japanese UHI modelling experts in Tokyo University for Japanese cities. The leading role of the two institutions (NU and LSHTM) in global health provides the advantage of wide-reaching impacts. Both institutions will work together on project implementation and the dissemination of findings, and stand to benefit from contributions to high priority research topics.

A Milojevic (LSHTM) will lead the supervisory team and coordinate with M Hashizume (NU / Tokyo Univ) and CFS Ng (NU). The student will be mostly based on at LSHTM for training and data analysis with repeated short-term (3 months cycles) research visits in Nagasaki for Japanese data processing, additional training and research experience. Full supervisory meeting will be conducted every fortnight remotely in addition to weekly face-to-face meeting between lead-supervisor and the candidate. Advisory committee members will be appointed either internal or external for specific area (such as UHI modelling and MCC network for further extension of target cities) as necessary.

Particular prior educational requirements for a student undertaking this project

MSc in public health, epidemiology or relevant area. Basic statistical skills and experience of quantitative data analyses using environment and/or health data are required. Confident epidemiological background and its application in designing the study/analysis, experience in advanced time series regression modelling, meta-analytical technique and R statistical software is desirable.

Skills we expect a student to develop/acquire whilst pursuing this project

The student will develop high-level quantitative skills in data analysis and regression modelling, in particular with complex linked large datasets. At the end of the joint PhD programme, the student will acquire sophisticated statistical methods, such as multi-level regression models, spatial analysis and health impact calculation, as well as general statistical computing potentially applicable in various research areas within and beyond environmental epidemiology. Additionally, the student is expected to gain experience to facilitate translation of epidemiological evidence into decisions for risk management, and be able to develop interdisciplinary skills linking health research and public policy. Communication and presentation skills for both academic and non-academic audience to transfer the findings of this project will also be developed whilst pursuing this project.