Summary: A new study reveals that people with multiple chronic physical conditions face a significantly higher risk of developing depression, especially when conditions like heart disease and diabetes co-occur. Researchers analyzed health data from over 142,000 adults and found that certain multimorbidity profiles more than doubled the chance of a depression diagnosis within 10 years.
Women with joint or bone issues and individuals with chronic lung, liver, or bowel conditions were also at elevated risk. The findings highlight the need for integrated care models that address both mental and physical health in tandem.
Key Facts:
- High-Risk Combinations: Cardiometabolic diseases like heart disease and diabetes greatly increase depression risk.
- Gender Disparity: Women with arthritis or joint issues are especially vulnerable.
- Systemic Shift Needed: Integrated care can better address physical and mental health together.
Source: University of Exeter
People with multiple long-term physical health conditions are at a significantly greater risk of developing depression, a study shows.
Researchers found that some combinations of illnesses – particularly cardiometabolic ones like diabetes and heart disease – could more than double the likelihood of a future depression diagnosis.
With multimorbidity – when patients live with two or more chronic conditions – continuing to put pressure on an already stretched healthcare system, experts say the findings highlight the need for integrated care models that address both mental and physical health.
Researchers from the University of Edinburgh used data from more than 142,000 people in the UK Biobank study to examine how physical illnesses interact to influence the risk of depression – a condition that often goes underdiagnosed in people managing long-term physical diseases.
Participants were aged 37-73 years and had at least one chronic physical condition but no history of depression.
Scientists used statistical clustering techniques to group individuals by their physical illness profiles and tracked how these clusters related to later diagnoses of depression.
One group, which included people experiencing the highest rates of physical illness also showed the highest risk of developing depression. This group had no single dominant illness, but rather a complex mix of issues.
People with both heart disease and diabetes were also found to be at high risk, as were those with chronic lung conditions like asthma or COPD – chronic obstructive pulmonary disease. Liver and bowel conditions also showed a noticeable link to depression in both men and women.
Women with joint and bone problems, such as arthritis, were particularly affected, but this pattern was not as prominent for men.
In the highest-risk groups, about one in 12 people developed depression over the next 10 years, compared with about one in 25 people without physical conditions.
While the biological burden of illness may play a role, researchers say social and systemic factors could also help explain why physical multimorbidity leads to worse mental health outcomes.
Lauren DeLong, lead author and PhD student at the University of Edinburgh’s School of Informatics, said: “We saw clear associations between physical health conditions and the development of depression, but this study is only the beginning.
“We hope our findings inspire other researchers to investigate and untangle the links between physical and mental health conditions.”
Bruce Guthrie, Professor of General Practice at the University of Edinburgh’s Advanced Care Research Centre, said: “Healthcare often treats physical and mental health as completely different things, but this study shows that we need to get better at anticipating and managing depression in people with physical illness.”
Professor Mike Lewis, NIHR’s Scientific Director of Innovation, said: “Harnessing the power of data to understand the impact of chronic conditions is going to transform the way we treat patients in the future.
“NIHR’s research in this area is helping to paint a full picture of what patients are dealing with, rather than just focusing on one health condition at a time.”
About this health and depression research news
Author: Guy Atkinson
Source: University of Exeter
Contact: Guy Atkinson – University of Exeter
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Cluster and survival analysis of UK biobank data reveals associations between physical multimorbidity clusters and subsequent depression” by Lauren DeLong et al. Nature Communications Medicine
Abstract
Cluster and survival analysis of UK biobank data reveals associations between physical multimorbidity clusters and subsequent depression
Background
Multimorbidity, the co-occurrence of two or more conditions within an individual, is a growing challenge for health and care delivery as well as for research. Combinations of physical and mental health conditions are highlighted as particularly important. Here, we investigated associations between physical multimorbidity and subsequent depression.
Methods
We performed a clustering analysis upon physical morbidity data for UK Biobank participants aged 37–73. Of 502,353 participants, 142,005 had linked general practice data with at least one baseline physical condition. Following stratification by sex (77,785 women; 64,220 men), we used four clustering methods and selected the best-performing based on clustering metrics.
We used Fisher’s Exact test to determine significant over-/under-representation of conditions within each cluster. Amongst people with no prior depression, we used survival analysis to estimate associations between cluster-membership and time to subsequent depression diagnosis.
Results
Our results show that the k-modes models perform best, and the over-/under-represented conditions in the resultant clusters reflect known associations. For example, clusters containing an overrepresentation of cardiometabolic conditions are amongst the largest (15.5% of whole cohort, 19.7% of women, 24.2% of men).
Cluster associations with depression vary from hazard ratio 1.29 (95% confidence interval 0.85–1.98) to 2.67 (2.24–3.17), but almost all clusters show a higher association with depression than those without physical conditions.
Conclusions
We show that certain groups of physical multimorbidity may be associated with a higher risk of subsequent depression. However, our findings invite further investigation into other factors, such as social considerations, which may link physical multimorbidity with depression.
