[TCRED-SANTE-CAUSES-DECES] Causes of death
Updated by provider on March 31, 2025 (12:00 AM).
[FREQ] Frequency
- [A] Annual
[INDICATEUR] Indicators
- [TAUX_MORTALITE] Mortality rate
- [TAUX_MORTALITE_STANDARDISE] Standardized mortality rate
[NATURE] Nature
- [TAUX] Rate
[CAUSE-DECES] Causes of death
- [DE_C01] Mortality rate - Infectious and parasitic diseases - All
- [DF_C02] Mortality rate - Tumours - Women
- [DF_C06] Mortality rate - Diseases of the circulatory system - Women
- [DF_C113] Mortality rate - Suicides - Women
- [DF_E00_E90] Mortality rate - Endocrine, nutritional and metabolic diseases - Women
- [DF_J00_U07] Mortality rate - Respiratory system diseases and COVID - Women
- [DF_V01_Y98] Mortality rate - External causes of mortality - Women
- [DH_C02] Mortality rate - Tumours - Men
- [DH_C06] Mortality rate - Diseases of the circulatory system - Men
- [DH_C113] Mortality rate - Suicides - Men
- [DH_E00_E90] Mortality rate - Endocrine, nutritional and metabolic diseases - Men
- [DH_J00_U07] Mortality rate - Respiratory system diseases and COVID - Men
- [DH_V01_Y98] Mortality rate - External causes of mortality - Men
[REF_AREA] Geographic areas
- [D01] 01 - Ain
- [D02] 02 - Aisne
- [D03] 03 - Allier
- [D04] 04 - Alpes-de-Haute-Provence
- [D05] 05 - Hautes-Alpes
- [D06] 06 - Alpes-Maritimes
- [D07] 07 - Ardèche
- [D08] 08 - Ardennes
- [D09] 09 - Ariège
- [D10] 10 - Aube
- [D11] 11 - Aude
- [D12] 12 - Aveyron
- [D13] 13 - Bouches-du-Rhône
- [D14] 14 - Calvados
- [D15] 15 - Cantal
- [D16] 16 - Charente
- [D17] 17 - Charente-Maritime
- [D18] 18 - Cher
- [D19] 19 - Corrèze
- [D21] 21 - Côte-d'Or
- [D22] 22 - Côtes-d'Armor
- [D23] 23 - Creuse
- [D24] 24 - Dordogne
- [D25] 25 - Doubs
- [D26] 26 - Drôme
- [D27] 27 - Eure
- [D28] 28 - Eure-et-Loir
- [D29] 29 - Finistère
- [D2A] 2A - Corse-du-Sud
- [D2B] 2B - Haute-Corse
- [D30] 30 - Gard
- [D31] 31 - Haute-Garonne
- [D32] 32 - Gers
- [D33] 33 - Gironde
- [D34] 34 - Hérault
- [D35] 35 - Ille-et-Vilaine
- [D36] 36 - Indre
- [D37] 37 - Indre-et-Loire
- [D38] 38 - Isère
- [D39] 39 - Jura
- [D40] 40 - Landes
- [D41] 41 - Loir-et-Cher
- [D42] 42 - Loire
- [D43] 43 - Haute-Loire
- [D44] 44 - Loire-Atlantique
- [D45] 45 - Loiret
- [D46] 46 - Lot
- [D47] 47 - Lot-et-Garonne
- [D48] 48 - Lozère
- [D49] 49 - Maine-et-Loire
- [D50] 50 - Manche
- [D51] 51 - Marne
- [D52] 52 - Haute-Marne
- [D53] 53 - Mayenne
- [D54] 54 - Meurthe-et-Moselle
- [D55] 55 - Meuse
- [D56] 56 - Morbihan
- [D57] 57 - Moselle
- [D58] 58 - Nièvre
- [D59] 59 - Nord
- [D60] 60 - Oise
- [D61] 61 - Orne
- [D62] 62 - Pas-de-Calais
- [D63] 63 - Puy-de-Dôme
- [D64] 64 - Pyrénées-Atlantiques
- [D65] 65 - Hautes-Pyrénées
- [D66] 66 - Pyrénées-Orientales
- [D67] 67 - Bas-Rhin
- [D68] 68 - Haut-Rhin
- [D69] 69 - Rhône
- [D70] 70 - Haute-Saône
- [D71] 71 - Saône-et-Loire
- [D72] 72 - Sarthe
- [D73] 73 - Savoie
- [D74] 74 - Haute-Savoie
- [D75] 75 - Paris
- [D76] 76 - Seine-Maritime
- [D77] 77 - Seine-et-Marne
- [D78] 78 - Yvelines
- [D79] 79 - Deux-Sèvres
- [D80] 80 - Somme
- [D81] 81 - Tarn
- [D82] 82 - Tarn-et-Garonne
- [D83] 83 - Var
- [D84] 84 - Vaucluse
- [D85] 85 - Vendée
- [D86] 86 - Vienne
- [D87] 87 - Haute-Vienne
- [D88] 88 - Vosges
- [D89] 89 - Yonne
- [D90] 90 - Territoire de Belfort
- [D91] 91 - Essonne
- [D92] 92 - Hauts-de-Seine
- [D93] 93 - Seine-Saint-Denis
- [D94] 94 - Val-de-Marne
- [D95] 95 - Val-d'Oise
- [D971] 971 - Guadeloupe
- [D972] 972 - Martinique
- [D973] 973 - French Guiana
- [D974] 974 - La Réunion
- [D976] 976 - Mayotte
- [FE] France
- [FM] Metropolitan France
- [F_H_IDF] Metropolitan France excluding Île-de-France
- [R11] Île-de-France
- [R24] Centre-Val de Loire
- [R27] Bourgogne-Franche-Comté
- [R28] Normandie
- [R32] Hauts-de-France
- [R44] Grand Est
- [R52] Pays de la Loire
- [R53] Bretagne
- [R75] Nouvelle-Aquitaine
- [R76] Occitanie
- [R84] Auvergne-Rhône-Alpes
- [R93] Provence-Alpes-Côte d'Azur
- [R94] Corse
[SEXE] Gender
- [1] Men
- [2] Women
[UNIT_MEASURE] Unit
- [P100000] per 100,000 inhabitants
[CORRECTION] Seasonal adjustment
- [BRUT] Uncorrected
[SERIE_ARRETEE] Stopped_series
- [FALSE] nO
Search filters
Frequency [FREQ] (1)
Indicators [INDICATEUR] (2)
Nature [NATURE] (1)
Causes of death [CAUSE-DECES] (13)
Geographic areas [REF_AREA] (117)
Gender [SEXE] (2)
Unit [UNIT_MEASURE] (1)
Seasonal adjustment [CORRECTION] (1)
Stopped_series [SERIE_ARRETEE] (1)
This dataset has 2,096 series:
- from
- 2018=NA
- to
- 2022=9.1
- min:
- 9.1
- max:
- 13.2
- avg:
- 11.15
- σ:
- 2.05
- from
- 2018=NA
- to
- 2022=15
- min:
- 15
- max:
- 15
- avg:
- 15
- σ:
- 0
- from
- 2018=NA
- to
- 2022=30.1
- min:
- 23.7
- max:
- 30.1
- avg:
- 26.9
- σ:
- 3.2
- from
- 2018=NA
- to
- 2022=30.3
- min:
- 28.9
- max:
- 30.3
- avg:
- 29.6
- σ:
- 0.7
- from
- 2018=NA
- to
- 2022=25.6
- min:
- 25.5
- max:
- 25.6
- avg:
- 25.55
- σ:
- 0.05
- from
- 2018=NA
- to
- 2022=30.7
- min:
- 28.1
- max:
- 30.7
- avg:
- 29.4
- σ:
- 1.3
- from
- 2018=NA
- to
- 2022=21.1
- min:
- 20
- max:
- 21.1
- avg:
- 20.55
- σ:
- 0.55
- from
- 2018=NA
- to
- 2022=15.1
- min:
- 15.1
- max:
- 17.6
- avg:
- 16.35
- σ:
- 1.25
- from
- 2018=NA
- to
- 2022=19
- min:
- 19
- max:
- 24.8
- avg:
- 21.9
- σ:
- 2.9
- from
- 2018=NA
- to
- 2022=11.2
- min:
- 11.2
- max:
- 18.1
- avg:
- 14.65
- σ:
- 3.45
Series code | 2020 | 2021 | 2022 |
---|---|---|---|
[A.TAUX_MORTALITE.TAUX.DE_C01.D01.1.P100000.BRUT.FALSE] | 13.2 | NA | 9.1 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D01.2.P100000.BRUT.FALSE] | 15 | NA | 15 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D02.1.P100000.BRUT.FALSE] | 23.7 | NA | 30.1 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D02.2.P100000.BRUT.FALSE] | 28.9 | NA | 30.3 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D03.1.P100000.BRUT.FALSE] | 25.5 | NA | 25.6 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D03.2.P100000.BRUT.FALSE] | 28.1 | NA | 30.7 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D04.1.P100000.BRUT.FALSE] | 20 | NA | 21.1 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D04.2.P100000.BRUT.FALSE] | 17.6 | NA | 15.1 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D05.1.P100000.BRUT.FALSE] | 24.8 | NA | 19 |
[A.TAUX_MORTALITE.TAUX.DE_C01.D05.2.P100000.BRUT.FALSE] | 18.1 | NA | 11.2 |
Showing results 1 - 10 / 2,096