The prevalence of multimorbidity, defined as the simultaneous presence of two or more diseases in the same individual, is increasing with the aging of the population and with increases in life-expectancy. Improving understanding of multimorbidity, and...
The prevalence of multimorbidity, defined as the simultaneous presence of two or more diseases in the same individual, is increasing with the aging of the population and with increases in life-expectancy. Improving understanding of multimorbidity, and considering multimorbidity in the estimation of disease burden, is becoming more important to ensure appropriate healthcare strategies that take account of multimorbidity.
This study analyzed data of adults aged 50 years and older derived from the cross-sectional, nationally representative 6th Korean National Health and Nutrition Examination Survey. We examined the prevalence of multimorbidity in Koreans aged 50 years and older, considering their socioeconomic status, and estimated the loss in the health-related quality of life due to multimorbidity. We also compared the performance of three models commonly used to adjust for multimorbidity―the additive, multiplicative, and maximum limit models―by determining the root mean squared error (RMSE) between the predicted and observed multimorbid disability weights. We also examined the impact of the adjustment for multimorbidity on the estimation of disease burden in the best-fitting model.
In this study, two or more chronic diseases were present in 26.8% of the participants aged 50 years and older, and in 37.9% of the participants aged 65 years and older. The most prevalent dyadic combination was hypertension and dyslipidemia in the 50 years and older group, versus hypertension and osteoarthritis in the 65 years and older age group. Greater multimorbidity, female gender, and lower socioeconomic status were associated with significantly lower EQ-5D index scores.
When comparing the performance of three multimorbidity adjustment models, the multiplicative adjustment model had the smallest RMSE between the predicted and observed multimorbid disability weights. Consideration of demographic and socioeconomic status in the multiplicative model generated a smaller RMSE and a larger R2. Adjustment for disability weight in the multiplicative model also resulted in a reduction in the total prevalence-based YLD.
Integrated and holistic healthcare with a patient-oriented approach, for earlier effective interventions targeting multimorbidity, is warranted. Appropriate adjustment for multimorbidity in the estimation of disease burden is important to set evidence-based priorities in healthcare governance and resource allocation.