10-Year Multimorbidity Trajectories in Older People Have Limited Benefit in Predicting Short-Term Health Outcomes in Comparison to Standard Multimorbidity Thresholds: A Population-Based Study

Abstract

Purpose

To identify multimorbidity trajectories among older adults and to compare their health outcome predictive performance with that of cross-sectional multimorbidity thresholds (eg, ≥2 chronic conditions (CCs)).

Patients and Methods

We performed a population-based longitudinal study with a random sample of 99,411 individuals aged >65 years on April 1, 2019. Using health administrative data, we calculated for each individual the yearly CCs number from 2010 to 2019 and constructed the trajectories with latent class growth analysis. We used logistic regression to determine the increase in predictive capacity (c-statistic) of multimorbidity trajectories and traditional cross-sectional indicators (≥2, ≥3, or ≥4 CCs, assessed in April 2019) over that of a baseline model (including age, sex, and deprivation). We predicted 1-year mortality, hospitalization, polypharmacy, and frequent general practitioner, specialist, or emergency department visits.

Results

We identified eight multimorbidity trajectories, each representing between 3% and 25% of the population. These trajectories exhibited trends of increasing, stable, or decreasing number of CCs. When predicting mortality, the 95% CI for the increase in the c-statistic for multimorbidity trajectories [0.032–0.044] overlapped with that of the ≥3 indicator [0.037–0.050]. Similar results were observed when predicting other health outcomes and with other cross-sectional indicators.

Conclusion

Multimorbidity trajectories displayed comparable health outcome predictive capacity to those of traditional cross-sectional multimorbidity indicators. Given its ease of calculation, continued use of traditional multimorbidity thresholds remains relevant for population-based multimorbidity surveillance and clinical practice.

Keywords:

• multimorbidity
• trajectories
• prevalence
• health outcome prediction
• population-based

Data Sharing Statement

The datasets generated and/or analysed during the current study are not publicly available due to data confidentiality requirements from the QICDSS. Code lists are available in supplementary data or in published papers.

Ethics Approval

The use of QICDSS for population health surveillance and methodological development has received approval from the custodians of the databases, the provincial Public Health Research Ethics Board and the Québec Commission responsible for safeguarding privacy and regulating access to information (Commission d’accès à l’information du Québec).

Acknowledgments

The authors are grateful to all QICDSS team members for their support. The abstract of this paper was presented at the 39th International Conference on Pharmacoepidemiology & Therapeutic Risk Management as an oral presentation with preliminary findings.

Disclosure

DT is supported by a research career award from the Fonds de recherche du Québec – Santé. YC is part of the Canadian Institutes of Health Research – postdoctoral fellowship. CS reports grants from Fonds de recherche du Québec - Santé, during the conduct of the study. The authors report no other conflicts of interest in this work.

Additional information

Funding

There is no funding to report.