Evidence map›Paper›PMID 39529031›Full record

ArticleBMC public health2024

Excess costs of depression among a population-based older adults with chronic diseases in Singapore.

Jia Wei Neo, Xue Ying Guo, Edimansyah Abdin, Janhavi Ajit Vaingankar, Siow Ann Chong, Mythily Subramaniam, Cynthia Chen

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jia Wei NeoSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore. e0320419@u.nus.edu.
Xue Ying GuoSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Edimansyah AbdinResearch Division, Institute of Mental Health, Singapore, Singapore.
Janhavi Ajit VaingankarResearch Division, Institute of Mental Health, Singapore, Singapore.
Siow Ann ChongResearch Division, Institute of Mental Health, Singapore, Singapore.
Mythily Subramaniam *Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Cynthia Chen *Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is limited evidence on the economic burden of depression among the older population in Singapore.

objectiveWe aim to evaluate the impact of depression on healthcare expenditure and productivity loss among older adults with chronic diseases in Singapore.

methodsUsing the data from the Well-being of the Singapore Elderly study (WiSE), a 2011 national representative survey of older adults aged 60 years and above, 2510 respondents were included in this study. The sample comprised 44% male and 56% female respondents with 75% respondents aged between 60 and 74 years old. Healthcare utilisation data was obtained from respondents and healthcare cost was tabulated by multiplying each service unit by the unit cost price. These services include care from polyclinic doctors, private general practitioners (GP), outpatient specialists and inpatient care. We modelled the relationship of healthcare cost and depression using two-part models (probit & generalised linear model - loglink and gamma distribution).

resultsFor total healthcare expenditure, older adults with both depression and chronic diseases were associated with an average annual incremental cost of $7940 (95% CI 1490-14400; p = 0.016), compared to those without these conditions. They were also associated with an average incremental cost of $257 (95% CI 38.7-475; p = 0.021) for primary care. Likewise, in the case of specialist outpatient clinics, they had an average incremental cost of $970 (95% CI 163-1780; p = 0.018). However, for inpatient setting, the average incremental cost of $6180 (95% CI 418-12800; p = 0.066) was not significant. Additionally, older adults with depression and chronic diseases contribute to an annual productivity loss of $676 (95% CI 346-1010; p < 0.001). DISCUSSION: This study provides evidence that there are significant incremental costs associated with depression amongst the older adults with chronic diseases in Singapore's primary healthcare setting. The increased somatic presentations among the depressed older adults and the underdiagnosis of depression in primary care may contribute to higher utilisation of healthcare resources which entail higher expenditure. This is one of the first studies to look at the cost of depression using a representative sample of Singaporean older adults and taking into account the multi-ethnic nature of the population. Analyses were restricted to a cross-sectional design, and data relied heavily on the accuracy of self-report utilisation on health care services which was subjected to recall bias.

conclusionDepression was found to inflate the total healthcare expenditure among older adults with chronic disease by two-fold. This study provides evidence that there are significant incremental costs associated with depression among the older adults with chronic diseases, demonstrating a need for more resources to improve systematic and clinical care for depressed older adults with chronic diseases.

Indexed as

DepressionHealth Care CostsHealth ExpendituresAgedAged, 80 and overChronic DiseaseCost of IllnessFemaleHumansMaleMiddle AgedSingaporeChronic diseasesDepressionHealthcare costOlder adults

Identifiers

PMID39529031
PMCPMC11555973

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.