Assessing the relative importance of correlates of loneliness in later life. Gaining insight using recursive partitioning

ABSTRACT

Objectives: Improving the design and targeting of interventions is important for alleviating loneliness among older adults. This requires identifying which correlates are the most important predictors of loneliness. This study demonstrates the use of recursive partitioning in exploring the characteristics and assessing the relative importance of correlates of loneliness in older adults.

Method: Using exploratory regression trees and random forests, we examined combinations and the relative importance of 42 correlates in relation to loneliness at age 68 among 2453 participants from the birth cohort study the MRC National Survey of Health and Development.

Results: Positive mental well-being, personal mastery, identifying the spouse as the closest confidant, being extrovert and informal social contact were the most important correlates of lower loneliness levels. Participation in organised groups and demographic correlates were poor identifiers of loneliness. The regression tree suggested that loneliness was not raised among those with poor mental wellbeing if they identified their partner as closest confidante and had frequent social contact.

Conclusion: Recursive partitioning can identify which combinations of experiences and circumstances characterise high-risk groups. Poor mental wellbeing and sparse social contact emerged as especially important and classical demographic factors as insufficient in identifying high loneliness levels among older adults.

KEYWORDS:

• Loneliness
• psycho-social interventions
• recursive partitioning
• random forest
• regression trees

Acknowledgments

The authors thank the study participants for their continuing participation in the MRC NSHD. They also thank members of the NSHD scientific and data collection teams who have been involved in the NSHD data collections.

Data used in this publication are available bona fide researchers upon request to the NSHD Data Sharing Committee via a standard application procedure. Furhter details can be found at http://www.nshd.mrc.ac.uk/data (dui: 10.5522/NSHD/Q101; doi: 10.5522/NSHD/Q102).

This study and MS and DK were funded by the UK MRC (program codes MC_UU_12019/1; MC_UU_12019/5).

Disclosure statement

No potential conflict of interest was reported by the authors.