[HTML][HTML] Clustering of chronic disease risks among people accessing community mental health services

C Regan, C Fehily, E Campbell, J Bowman… - Preventive Medicine …, 2022 - Elsevier
C Regan, C Fehily, E Campbell, J Bowman, J Faulkner, C Oldmeadow, K Bartlem
Preventive Medicine Reports, 2022Elsevier
This study identified clusters of chronic disease risks and explored associations between
clusters and demographic characteristics and mental health conditions, among people
accessing community mental health services. Data from a cross-sectional telephone survey
of Australian mental health consumers (n= 567) were analysed. Clusters were identified
based on tobacco smoking (53.5%), harmful chronic alcohol consumption (20.1%), harmful
acute alcohol consumption (43.5%), inadequate fruit and vegetable intake (66.0%) …
Abstract
This study identified clusters of chronic disease risks and explored associations between clusters and demographic characteristics and mental health conditions, among people accessing community mental health services. Data from a cross-sectional telephone survey of Australian mental health consumers (n = 567) were analysed. Clusters were identified based on tobacco smoking (53.5%), harmful chronic alcohol consumption (20.1%), harmful acute alcohol consumption (43.5%), inadequate fruit and vegetable intake (66.0%), inadequate physical activity (75.5%), inadequate strength activity (81.8%), and high body mass index (BMI) (67.9%), using latent class analysis. Multinomial logistic regression examined associations between cluster membership and participant characteristics. Three groups were identified: Cluster 1 (19.05%) had < 0.5 probabilities for most risks; Cluster 2 (34.04%) had high probabilities of all risks, particularly tobacco smoking and both types of harmful alcohol consumption; and Cluster 3 (46.91%) had high probabilities of both inadequate physical and strength activity, inadequate fruit and vegetable intake, and high BMI. Compared to Cluster 1 membership, participants with higher education were less likely to be in either Cluster 2 or 3, females or those over 55 were more likely to be in Cluster 3, those with a substance use disorder were more likely to be in Cluster 2, and those with a personality disorder were less likely to be in Cluster 3. The clustering patterns reinforce the importance of addressing multiple chronic disease risks for people with a mental health condition. Preventive care interventions targeting clusters of risks may help reduce the burden of chronic disease among this high-risk population.
Elsevier
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