Wang Z, Boulanger L, Berger D, et al. - Utilizing data from the Canadian Longitudinal Study on Aging (CLSA), researchers focused on creating as well as internally validating a measure of multimorbidity burden. This study involved a development dataset and a validation dataset. By employing logistic regression models, experts predicted overnight hospitalisation in the last 12 months in the development dataset (random two-thirds of the total) and utilized these to develop 10 multimorbidity indices (5 models, each treated with and without an age interaction term). Consideration was given to 35 chronic conditions for inclusion in these models, over and above age and gender. In this work, alternative methods were inquired to ascertain the multimorbidity burden of people, tailored to the CLSA. The strongest calibration of an absolute count of conditions, along with an age interaction term, for overnight hospitalisation in the last 12 months was revealed. The likely applicability of the utility of an age interaction term in recording multimorbidity burden to the study of chronic disease in cohorts other than the CLSA was suggested.