Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction

Bibliographic Data

ID22067601
AuthorsFederico Rea (0000-0001-7988-5101, University of Milano-Bicocca, corresponding author), Mauro Ferrante (0000-0003-1287-5851, University of Palermo), Salvatore Scondotto (0000-0001-7620-3080, Regione Siciliana), Giovanni Corrao (0000-0002-1034-8444, Ministero della Salute)
Year2023
Volume11
Pages1128377-1128377
Publication date2023-05-16
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1128377
PMID37261238
OpenAlexW4376646079
LanguageEN
References cited29

Background: The stratification of the general population according to health needs allows to provide better-tailored services. A simple score called Multisource Comorbidity Score (MCS) has been developed and validated for predicting several outcomes. The aim of this study was to evaluate whether the ability of MCS in predicting 1-year mortality improves by incorporating socioeconomic data (as measured by a deprivation index). Methods: Beneficiaries of the Italian National Health Service who in the index year (2018) were aged 50-85 years and were resident in the Sicily region for at least 2 years were identified. For each individual, the MCS was calculated according to his/her clinical profile, and the deprivation index of the census unit level of the individual's residence was collected. Frailty models were fitted to assess the relationship between the indexes (MCS and deprivation index) and 1-year mortality. Akaike information criterion and Bayesian information criterion statistics were used to compare the goodness of fit of the model that included only MCS and the model that also contained the deprivation index. The models were further compared by means of the area under the receiver operating characteristic curve (AUC). Results: The final cohort included 1,062,221 individuals, with a mortality rate of 15.6 deaths per 1,000 person-years. Both MCS and deprivation index were positively associated with mortality.The goodness of fit statistics of the two models were very similar. For MCS only and MCS plus deprivation index models, Akaike information criterion were 17,013 and 17,038, respectively, whereas Bayesian information criterion were 16,997 and 17,000, respectively. The AUC values were 0.78 for both models. Conclusion: The present study shows that socioeconomic features as measured by the deprivation index did not improve the capability of MCS in predicting 1-year risk of death. Future studies are needed to investigate other sources of data to enhance the risk stratification of populations

Comorbidity · Chronic Disease Management Strategies · Computer Science · Frailty in Older Adults · Health disparities and outcomes · Medicine · Internal Medicine

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