Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach
Abstract Background Years of life lost (YLL) due to premature mortality is an important metric to assess the fatal impact of diseases. The main objectives of this study were to apply the four-step probabilistic method to redistribute ill-defined deaths (IDDs) and to quantify the premature mortality...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12889-025-23559-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849389206949855232 |
|---|---|
| author | Romana Haneef Aline Scohy Nour Mahrouseh Elise Coudin Panayotis Constantinou Antoine Rachas Tina Lesnik Grant M. A. Wyper Brecht Devleesschauwer |
| author_facet | Romana Haneef Aline Scohy Nour Mahrouseh Elise Coudin Panayotis Constantinou Antoine Rachas Tina Lesnik Grant M. A. Wyper Brecht Devleesschauwer |
| author_sort | Romana Haneef |
| collection | DOAJ |
| description | Abstract Background Years of life lost (YLL) due to premature mortality is an important metric to assess the fatal impact of diseases. The main objectives of this study were to apply the four-step probabilistic method to redistribute ill-defined deaths (IDDs) and to quantify the premature mortality burden at regional level in France for 2017. Methods We used the statistical database on medical causes of death derived from death certificate collection and coded by the Center for Epidemiology on Medical Causes of deaths (INSERM-CépiDc). First, we mapped the specific ICD-10 codes that define the underlying cause of death (CoD) to the Global Burden of Disease (GBD) cause list. Second, identified IDDs were redistributed to specific ICD-10 codes. A four-step probabilistic redistribution developed for the Belgium Burden of Disease (BeBOD) study was adopted to fit the French context: redistribution using predefined ICD codes, package redistribution using multiple causes of death data, internal redistribution, and redistribution to all causes. Finally, Standard Expected Years of Life Lost (SEYLL) and age-standardized SEYLL rates (ASYR) were calculated at regional level, using the GBD 2019 reference life table. Results In France, 36% of all deaths were IDDs in 2017. The majority was redistributed using predefined ICD codes (14%), followed by the package redistribution using multiple causes of death data (11%), all-cause redistribution (11%) and internal redistribution (< 1%). The total number of SEYLL was 9.6 million for all causes, (4.1 million in females [43%] and 5.5 million in males [57%]). Tracheal, bronchus, and lung cancer ranked first (10%), followed by ischemic heart disease (7%), and Alzheimer’s disease and other dementias (6%) in terms of SEYLL. For all causes, we observed the lowest ASYRs in Corse for females (8970 per 100 000) and in Ile-de-France for males (16 109 per 100 000). Conclusions We quantified the full mortality burden for the first time in France at regional level, based on a new probabilistic redistribution method developed by researchers from Sciensano before COVID-19 pandemic. These estimates are important for future investigations on the contribution of social inequalities and risk factors to all-cause mortality in France with a focus on regional differences. |
| format | Article |
| id | doaj-art-6f8e46ff76764a8fad11e1ef6da5dd1a |
| institution | Kabale University |
| issn | 1471-2458 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| spelling | doaj-art-6f8e46ff76764a8fad11e1ef6da5dd1a2025-08-20T03:42:02ZengBMCBMC Public Health1471-24582025-07-0125111610.1186/s12889-025-23559-6Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approachRomana Haneef0Aline Scohy1Nour Mahrouseh2Elise Coudin3Panayotis Constantinou4Antoine Rachas5Tina Lesnik6Grant M. A. Wyper7Brecht Devleesschauwer8Department of Non-Communicable Diseases and Injuries, Santé Publique FranceDepartment of Epidemiology and Public HealthDepartment of Public Health and Epidemiology, Faculty of Medicine, University of DebrecenCentre d’épidémiologie Sur Les Causes Médicales de Décès de L’Institut National de La Recherche Médicale (INSERM - CépiDc)Department of Strategy, Studies and Statistics, French National Health Insurance: Caisse Nationale de L’assurance Maladie (Cnam)Department of Strategy, Studies and Statistics, French National Health Insurance: Caisse Nationale de L’assurance Maladie (Cnam)National Institute of Public HealthSchool of Health and Wellbeing, University of GlasgowDepartment of Epidemiology and Public HealthAbstract Background Years of life lost (YLL) due to premature mortality is an important metric to assess the fatal impact of diseases. The main objectives of this study were to apply the four-step probabilistic method to redistribute ill-defined deaths (IDDs) and to quantify the premature mortality burden at regional level in France for 2017. Methods We used the statistical database on medical causes of death derived from death certificate collection and coded by the Center for Epidemiology on Medical Causes of deaths (INSERM-CépiDc). First, we mapped the specific ICD-10 codes that define the underlying cause of death (CoD) to the Global Burden of Disease (GBD) cause list. Second, identified IDDs were redistributed to specific ICD-10 codes. A four-step probabilistic redistribution developed for the Belgium Burden of Disease (BeBOD) study was adopted to fit the French context: redistribution using predefined ICD codes, package redistribution using multiple causes of death data, internal redistribution, and redistribution to all causes. Finally, Standard Expected Years of Life Lost (SEYLL) and age-standardized SEYLL rates (ASYR) were calculated at regional level, using the GBD 2019 reference life table. Results In France, 36% of all deaths were IDDs in 2017. The majority was redistributed using predefined ICD codes (14%), followed by the package redistribution using multiple causes of death data (11%), all-cause redistribution (11%) and internal redistribution (< 1%). The total number of SEYLL was 9.6 million for all causes, (4.1 million in females [43%] and 5.5 million in males [57%]). Tracheal, bronchus, and lung cancer ranked first (10%), followed by ischemic heart disease (7%), and Alzheimer’s disease and other dementias (6%) in terms of SEYLL. For all causes, we observed the lowest ASYRs in Corse for females (8970 per 100 000) and in Ile-de-France for males (16 109 per 100 000). Conclusions We quantified the full mortality burden for the first time in France at regional level, based on a new probabilistic redistribution method developed by researchers from Sciensano before COVID-19 pandemic. These estimates are important for future investigations on the contribution of social inequalities and risk factors to all-cause mortality in France with a focus on regional differences.https://doi.org/10.1186/s12889-025-23559-6Cause of deathMortalityYears of life lostYLLRedistributionIll-defined deaths |
| spellingShingle | Romana Haneef Aline Scohy Nour Mahrouseh Elise Coudin Panayotis Constantinou Antoine Rachas Tina Lesnik Grant M. A. Wyper Brecht Devleesschauwer Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach BMC Public Health Cause of death Mortality Years of life lost YLL Redistribution Ill-defined deaths |
| title | Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach |
| title_full | Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach |
| title_fullStr | Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach |
| title_full_unstemmed | Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach |
| title_short | Estimating years of life lost due to premature mortality at regional level in France in 2017, using a probabilistic redistribution approach |
| title_sort | estimating years of life lost due to premature mortality at regional level in france in 2017 using a probabilistic redistribution approach |
| topic | Cause of death Mortality Years of life lost YLL Redistribution Ill-defined deaths |
| url | https://doi.org/10.1186/s12889-025-23559-6 |
| work_keys_str_mv | AT romanahaneef estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT alinescohy estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT nourmahrouseh estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT elisecoudin estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT panayotisconstantinou estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT antoinerachas estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT tinalesnik estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT grantmawyper estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach AT brechtdevleesschauwer estimatingyearsoflifelostduetoprematuremortalityatregionallevelinfrancein2017usingaprobabilisticredistributionapproach |