Multiple Chronic Conditions (Multimorbidity): From Zero to Many | Duke Kunshan University
Multiple Chronic Conditions (Multimorbidity): From Zero to Many
Speaker: 
Dr. Xiaolin Xu

Senior Research Fellow at the National Institute for Data Science in Health and Medicine, Zhejiang University; Honorary Fellow in the School of Public Health, The University of Queensland (Australia)

Nov 19th 2019 12:00 to 13:00
Room 3107, Academic Building
Monday, November 4, 2019 - 10:45

Summary of talk:

As the population ages, an increasing number of people lived or will live with multiple chronic conditions (also known as multimorbidity). Multimorbidity affects more than half of older people and has been recognized as the most common “chronic condition”. Multimorbidity is associated with decreased quality of life, increased health services use and cost, disability, and premature mortality. Tackling multimorbidity is one of the key challenges facing governments and health systems globally.

This presentation will focus on three topics: 1) Multimorbidity is common and is becoming the norm; 2) How people progress from a healthy state to one with multimorbidity? 3) What can we do to prevent or slow down the progression? This program of research is based on literature reviews and includes quantitative analyses of prospective data from the Australian Longitudinal Study on Women’s Health.

Brief Biography:

Dr. Xiaolin Xu is a Senior Research Fellow at the National Institute for Data Science in Health and Medicine, Zhejiang University. He is also an Honorary Fellow in the School of Public Health, The University of Queensland (Australia). He was formerly a Research Assistant in the Global Health Research Center at Duke Kunshan University. He also worked and interned in a healthcare consulting company in Shanghai and London, and the Headquarter of the World Health Organization in Geneva. His PhD research applies longitudinal data analysis and life-course epidemiology to examine the development and progression of multimorbidity in three generations of Australian women, and to explore how this progression is modified by physiological, behavioural, and social risk factors. Results from his PhD studies have been summarised in eight manuscripts, and seven of them have been published in peer-reviewed journals (e.g., PLoS Medicine, Ageing Research Reviews, International Journal of Obesity). Currently, he is working on prediction models and precision medicine for cancer and major chronic diseases using big data.