ArticleScientific reports2019
Investigation of multimorbidity and prevalent disease combinations in older Irish adults using network analysis and association rules.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
62 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Social determinants of multimorbidity patterns: A systematic review.Frontiers in public health · 2023Pooled it
- Pooled it
- Pooled it
- Age-period-cohort analysis of multimorbidity prevalence among Chinese older adults: from 2002 to 2022.GeroScience · 2026Article
- An ageing biomarker signature predicts chronic disease cluster trajectories, physical function and mortality: validation in the TILDA and HRS cohorts.Age and ageing · 2026Article
- Article
- Exploring the genetic architecture of multiple long-term conditions using a genome-wide association study in the UK Biobank population.Scientific reports · 2025Article
- Investigation of multimorbidity patterns and association rules in patients with type 2 diabetes mellitus using association rules mining algorithm.Scientific reports · 2025Article
- Temporal multimorbidity patterns and cluster identification: a longitudinal analysis of administrative data.BMC medicine · 2025Article
- Prediction of Multimorbidity Network Evolution in Middle-Aged and Elderly Population Based on CE-GCN.Interdisciplinary sciences, computational life sciences · 2025Review
- Identifying research priorities for chronic disease management in primary care: results of an Irish James Lind Alliance Priority Setting Partnership.BMC primary care · 2025Article
- Characterizing patients at higher cardiovascular risk for prescribed stimulants: Learning from health records data with predictive analytics and data mining techniques.Computers in biology and medicine · 2025Article
- Comorbidity and cost burden among ischemic stroke inpatients aged 60 years and older in middle-high-income region in China: a multicenter cross-sectional study.Frontiers in public health · 2025Article
- Identification of population multimorbidity patterns in 3.9 million patients from Bogota in 2018.Global epidemiology · 2024Article
- Health knowledge needs of administrative staff and related influencing factors: a cross-sectional data from Yuxi, China.Scientific reports · 2024Article
- Choices of measures of association affect the visualisation and composition of the multimorbidity networks.BMC medical research methodology · 2024Article
- An investigation on the prevalence and patterns of multi-morbidity among a group of slum-dwelling older women of Kolkata, India.BMC geriatrics · 2024Article
- A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.JMIR public health and surveillance · 2024Article
- Interactions between patterns of multimorbidity and functional status among hospitalized older patients: a novel approach using cluster analysis and association rule mining.Journal of translational medicine · 2024Article
- The diabetes mellitus multimorbidity network in hospitalized patients over 50 years of age in China: data mining of medical records.BMC public health · 2024Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multimorbidity (the presence of multiple medical conditions) is well known to increase with age. People with multimorbidities often have higher physical and functional decline as well as increased mortality. Despite growing evidence that integrated and collaborative care improves many undesirable outcomes of multimorbidity, the majority of health systems are based around treating individual diseases. A pattern analysis of comorbidities using network graphs and a novel use of association rules was conducted to investigate disease associations on 6101 Irish adults aged 50+. The complex network of morbidities and differences in the prevalence and interactions of these morbidities by sex was also assessed. Gender specific differences in disease prevalence was found for 22/31 medical conditions included in this study. Females had a more complex network of disease associations than males with strong associations found between arthritis, osteoporosis and thyroid issues among others. To assess the strength of these associations we provide probabilities of being diagnosed with a comorbid condition given the presence of an index morbidity for 639 pairwise combinations. This information can be used to guide clinicians in deciding which comorbidities should be incorporated into comprehensive assessments in addition to anticipating likely future morbidities and thus developing prevention strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.