- Research led by PhD student Alisha Suhag, with Professor John Holmes and Professor Thomas L Webb, identifies new clusters of specific health behaviours and demographic characteristics in older adults and how they change over time
- The findings of this questions previous studies that suggest a linear relationship between the number of risky behaviors that people engage in and health outcomes
Research from the Healthy Lifespan Institute identified subgroups of people with different health behaviours and their association with multimorbidity in older adults in England.
Multimorbidity is the presence of two or more of the chronic health conditions that create disability and poor quality of life in old age.
Many studies on multimorbidity focus on analysing the health behaviours of an ageing population by adding up the number of risky behaviours 鈥 such as drinking alcohol, low levels of physical activity and smoking 鈥 that a person is engaging with. However, this approach doesn鈥檛 consider the possibility that specific combinations of behaviour, or patterns of behaviour over time, can increase the risk of disease.
A led by PhD student Alisha Suhag from the Healthy Lifespan Institute at the University of 91探花 was the first to identify subgroups, or clusters, of health behaviours and examine how they are associated with disease, as well as how they change over time.
The study analysed the data of adults over the age of 50 living in England collected as part of the English Longitudinal Study of Ageing. It identified 7 different groups based on their patterns of health behaviour over time. Some findings were predictable, such as finding that the cluster containing smokers had a higher prevalence of respiratory disorders.
But the research also highlighted new relationships between health behaviours and multimorbidity, such as identifying an 鈥Abstainer yet Inactive鈥 group. This group was predominantly female, and while they only exhibited a single risky behaviour (having low levels of physical activity), they showed higher levels of multimorbidity, complex multimorbidity, and endocrine disorders, even when compared to other clusters that engaged in two or three risky behaviours. 鈥淭his questions previous findings which suggest a more linear relationship between the number of risky behaviours that people engage with and their health outcomes鈥 explains Alisha Suhag.
鈥淭his study allowed us to identify high-risk subgroups which had previously been overlooked. Our research showed that some groups actually had worse health outcomes than the clusters you would have expected to rate higher, such as Inactive, Heavy drinkers or the Poor diet and Inactive cluster. On the other hand, Low-risk yet Heavy drinkers had a lower prevalence of most health conditions studied, even lower than the overall Low risk cluster. By identifying the specific health behaviour profiles and demographic characteristics of these groups, interventions can be targeted to high-risk subgroups鈥 she adds.
The study was funded through a Healthy Lifespan Institute studentship awarded to PhD student Alisha Suhag at the University of 91探花.