Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction
BackgroundThe 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 a...
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Frontiers Media S.A.
2023-05-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128377/full |
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| author | Federico Rea Federico Rea Mauro Ferrante Salvatore Scondotto Giovanni Corrao Giovanni Corrao Giovanni Corrao |
| author_facet | Federico Rea Federico Rea Mauro Ferrante Salvatore Scondotto Giovanni Corrao Giovanni Corrao Giovanni Corrao |
| author_sort | Federico Rea |
| collection | DOAJ |
| description | BackgroundThe 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).MethodsBeneficiaries 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).ResultsThe 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.ConclusionThe 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. |
| first_indexed | 2024-04-09T12:30:55Z |
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| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-09T12:30:55Z |
| publishDate | 2023-05-01 |
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| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-de2da0866c0c45c69534bd04c152bf8a2023-05-16T05:13:43ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-05-011110.3389/fpubh.2023.11283771128377Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality predictionFederico Rea0Federico Rea1Mauro Ferrante2Salvatore Scondotto3Giovanni Corrao4Giovanni Corrao5Giovanni Corrao6National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyLaboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, ItalyDepartment of Culture and Society, University of Palermo, Palermo, ItalyEpidemiologic Observatory, Sicily Regional Health Service, Palermo, ItalyNational Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyLaboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, ItalyDirectorate General for Health, Lombardy Region, Milan, ItalyBackgroundThe 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).MethodsBeneficiaries 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).ResultsThe 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128377/fullpopulation-based studycomorbidityprognostic scorehealthcaremortalitysocioeconomic position |
| spellingShingle | Federico Rea Federico Rea Mauro Ferrante Salvatore Scondotto Giovanni Corrao Giovanni Corrao Giovanni Corrao Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction Frontiers in Public Health population-based study comorbidity prognostic score healthcare mortality socioeconomic position |
| title | Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| title_full | Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| title_fullStr | Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| title_full_unstemmed | Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| title_short | Small-area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| title_sort | small area deprivation index does not improve the capability of multisource comorbidity score in mortality prediction |
| topic | population-based study comorbidity prognostic score healthcare mortality socioeconomic position |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1128377/full |
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