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Depression

“Jolly fat” or “sad fat”: a systematic review and meta-analysis of the association between obesity and depression among community-dwelling older adults

, , &
Pages 13-25 | Received 06 May 2020, Accepted 26 Nov 2020, Published online: 10 Dec 2020
 

Abstract

Objective

To review the evidence and explore the association between obesity and depression in community-dwelling older adults.

Methods

We searched 6 electronic databases from inception to November 28, 2019. Observational studies investigating the association between obesity and depression among community-dwelling older adults aged 60years or older were included. Two reviewers independently screened the studies, extracted the data and assessed the quality of the studies. The eligible studies were meta-analysed using the Comprehensive Meta-analysis Version 3.0.

Results

Among the 16,059 studies identified from these databases, 19 studies meeting the inclusion criteria were included, of which 14 were meta-analysed. Meta-analyses showed that older adults who were overweight (pooled odds ratio: 0.847, 95% CI:0.789-0.908, p<0.001) or obesity (pooled odds ratio: 0.795, 95% CI:0.658-0.960, p=0.017) – assessed using the body mass index – were significantly less likely to be depressed than their counterparts with a normal weight. No significant association between obesity (as measured via waist circumference) and depression was detected (pooled odds ratio: 0.722, 95% CI:0.465-1.119, p=0.145) in this group population. The subgroup analyses demonstrated that both female and male older adults with overweight/obesity were significantly less likely to have depression.

Conclusions

The “jolly fat” hypothesis is deemed to be applicable among community-dwelling older adults. Older adults might, therefore, be encouraged to increase their body weight above the normal level to be mentally healthy. Monitoring intentional weight loss among older adults should be reinforced for public health strategies.

Acknowledgements

The authors would like to acknowledge Dr. Wilson WS Tam, the biostatistician from National University of Singapore, for his guidance on data analysis of this review paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

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