Effectiveness of interventions for managing multiple high-burden chronic diseases in older adults: a systematic review and meta-analysis
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INTRODUCTION: More than half of older adults (age ≥ 65 yr) have 2 or more high-burden multimorbidity conditions (i.e., highly prevalent chronic diseases, which are associated with increased health care utilization; these include diabetes [DM], dementia, depression, chronic obstructive pulmonary disease [COPD], cardiovascular disease [CVD], arthritis, and heart failure [HF]), yet most existing interventions for managing chronic disease focus on a single disease or do not respond to the specialized needs of older adults. We conducted a systematic review and meta-analysis to identify effective multimorbidity interventions compared with a control or usual care strategy for older adults. METHODS: We searched bibliometric databases for randomized controlled trials (RCTs) evaluating interventions for managing multiple chronic diseases in any language from 1990 to December 2017. The primary outcome was any outcome specific to managing multiple chronic diseases as reported by studies. Reviewer pairs independently screened citations and full-text articles, extracted data and assessed risk of bias. We assessed statistical and methodological heterogeneity and performed a meta-analysis of RCTs with similar interventions and components. RESULTS: We included 25 studies (including 15 RCTs and 6 cluster RCTs) (12 579 older adults; mean age 67.3 yr). In patients with [depression + COPD] or [CVD + DM], care-coordination strategies significantly improved depressive symptoms (standardized mean difference −0.41; 95% confidence interval [CI] −0.59 to −0.22; I2 = 0%) and reduced glycosylated hemoglobin (HbA1c) levels (mean difference −0.51; 95% CI −0.90 to −0.11; I2 = 0%), but not mortality (relative risk [RR] 0.79; 95% CI 0.53 to 1.17; I2 = 0%). Among secondary outcomes, care-coordination strategies reduced functional impairment in patients with [arthritis + depression] (between-group difference −0.82; 95% CI −1.17 to −0.47) or [DM + depression] (between-group difference 3.21; 95% CI 1.78 to 4.63); improved cognitive functioning in patients with [DM + depression] (between-group difference 2.44; 95% CI 0.79 to 4.09) or [HF + COPD] (p = 0.006); and increased use of mental health services in those with [DM + (CVD or depression)] (RR 2.57; 95% CI 1.90 to 3.49; I2 = 0%). INTERPRETATION: Subgroup analyses showed that older adults with diabetes and either depression or cardiovascular disease, or with coexistence of chronic obstructive pulmonary disease and heart failure, can benefit from care-coordination strategies with or without education to lower HbA1c, reduce depressive symptoms, improve health-related functional status, and increase the use of mental health services. Protocol registration: PROSPERO-CRD42014014489
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There is a higher prevalence of hypertension, diabetes, obesity, physical inactivity, smoking, excessive alcohol, less education, traumatic brain injury and exposure to air pollution in those from lower socioeconomic groups in high-income countries, and with lower income level.
“There is a higher prevalence of hypertension, diabetes, obesity, physical inactivity, smoking, excessive alcohol, less education, traumatic brain injury (TBI) and exposure to air pollution in those from lower socioeconomic groups in HICs, and with lower income level.(48-50)”
From Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission (2024) · cites this paper as [49]
The Results section describes chronic-disease clusters and interventions in older adults, but does not compare their prevalence by socioeconomic or income level. Searches for socioeconomic status, income, traumatic brain injury, and air pollution found no passage addressing the claimed pattern of risk factors in high-income countries. (LLM, conf=0.76)
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eHealth in Care Coordination for Older Adults Living at Home: Scoping Review
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Framing physical literacy for aging adults: an integrative review
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Age Friendly Care: What do Community Aging Services Professionals Need to Know?
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What we need to learn about multimorbidity
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Demographics and Oral Health Care Utilization for Older Adults
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Learning from suicide deaths in Harris County, Texas
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- Authors
- Kastner, M., Cardoso, R., Lai, Y., Treister, V., Hamid, J. S., Hayden, L., Wong, G., Ivers, N. M., Liu, B., Marr, S., Holroyd-Leduc, J., & Straus, S. E.
- Affiliations
- St. Michael's Hospital (CA)
- ORCID
- Venue
- Canadian Medical Association Journal
- Publisher
- CMA Impact Inc.
- Published
- 2018-08-26
- Volume
- 190
- Issue
- 34
- Pages
- E1004-E1012
- ISSN
- 0820-3946 (ISSN-L)
- 1488-2329
- PMC
- PMC6110649
- OpenAlex
- W2888528917
- Cited by
- 154
- References
- 72
- Citations by year
- 2026: 13 · 2025: 12 · 2024: 26 · 2023: 29 · 2022: 16 · 2021: 19 · 2020: 21 · 2019: 16 · 2018: 2
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Canadian Medical Association Journal (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- multimorbidity, chronic disease management, older adults, care coordination, depression, diabetes mellitus, chronic obstructive pulmonary disease, cardiovascular disease, heart failure, arthritis, dementia, functional disability, cognitive function, HbA1c, mortality, quality of life, health care utilization, intervention effectiveness, usual care comparison, secondary care, hospital readmission
- MeSH terms
- Physical Functional Performance, Aged, Chronic Disease, Depression, Humans, Mental Health Services, Patient Care Management, Quality of Life, Comorbidity, Randomized Controlled Trials as Topic, Cost of Illness
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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