ArticleBMC medical research methodology2020
Adjusting for comorbidity in incidence-based DALY calculations: an individual-based modeling approach.
Article in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 19 citations in OpenAlex.
- Comorbidity-adjusted life expectancy using comprehensive summary measures of medical history: nationwide, population-based study in Sweden.European journal of epidemiology · 2026Article
- Enhancing regional disease burden estimates: insights from the comparison of Global Burden of Disease and China's notifiable infectious diseases data with policy implications (2010-2020).Infectious diseases of poverty · 2025Article
- Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data.Population health metrics · 2025Article
- Measuring the disease burden of seasonal influenza in Germany 2015 - 2020 using the incidence-based disability-adjusted life years (DALYs).BMC infectious diseases · 2025Article
- Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis.Journal of dairy science · 2024Article
- The health and economic burden of musculoskeletal disorders in Belgium from 2013 to 2018.Population health metrics · 2023Article
- The contribution of general medical conditions to the non-fatal burden of mental disorders: register-based cohort study in Denmark.BJPsych open · 2022Article
- A scoping review of burden of disease studies estimating disability-adjusted life years due to Taenia solium.PLoS neglected tropical diseases · 2022Article
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe co-occurrence of two or more medical conditions in the same individual is not uncommon. If disability-adjusted life year (DALY) calculations are carried out for each condition separately, multimorbidity may lead to an overestimation of the morbidity component, the Years Lived with Disability (YLD). Adjusting for comorbidity may be straightforward if all symptoms have same onset and duration; however, when the comorbid health states occur at different time points, an analytical solution to the comorbidity problem becomes more complex. The aim of this study was to develop an individual-based modelling (IBM) approach to adjust incidence-based disease burden estimation for multimorbidity that allows simulating hypothetical individuals and tracking their disease history, including possible comorbidities, over time.
methodsWe demonstrated the IBM approach using an example of external comorbidity, i.e., colon cancer comorbid with healthcare-associated pneumonia (HAP) and by assuming an independent multiplicative model. First, each cumulative progression probabilities were converted to a daily transition probabilities. Second, disability weights for simultaneously experienced health states and duration in each health state were determined. Third, YLD, adjusted for comorbidity, was calculated at every time step. We simulated a cohort of 1000 colorectal cancer patients aged 65 years. Ninety-five percent uncertainty intervals around median YLD values were estimated by Monte Carlo methods.
resultsThe median estimated YLD per 1000 cases (due to both cancer and HAP) adjusted for co-morbidity was 545 YLD/1000 (95% interval: 513-585). The impact of not adjusting disability weights for co-existent health states varied from minimal to small; YLD for colorectal cancer would be overestimated only slightly - by 1.6 YLD/1000 - by not adjusting for concurrent HAP. YLD for those HAP patients who have concurrent early-stage colorectal cancer would be overestimated by 2.3 YLD/1000.
conclusionsThe computation of disease burden in the presence of multimorbidity using the incidence-based DALY approach can be handled through IBM. Our approach can be extended to other, more complicated multimorbidity scenarios which are responsible for a high current global disease burden, such as tuberculosis and HIV infection.
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