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Global, Regional, and National Disability-Adjusted Life-Years (Dalys) for 315 Diseases and Injuries and Healthy Life Expectancy (Hale), 1990–2015: A Systematic Analysis for the Global Burden of Disease Study 2015 Publisher Pubmed



Kassebaum NJ1 ; Arora M1 ; Barber RM1 ; Brown J1 ; Carter A1 ; Casey DC1 ; Charlson FJ1, 9, 12 ; Coates MM1 ; Coggeshall M1 ; Cornaby L1 ; Dandona L1, 14 ; Dicker DJ1 ; Erskine HE1, 9, 12 ; Ferrari AJ1, 9, 12 Show All Authors
Authors
  1. Kassebaum NJ1
  2. Arora M1
  3. Barber RM1
  4. Brown J1
  5. Carter A1
  6. Casey DC1
  7. Charlson FJ1, 9, 12
  8. Coates MM1
  9. Coggeshall M1
  10. Cornaby L1
  11. Dandona L1, 14
  12. Dicker DJ1
  13. Erskine HE1, 9, 12
  14. Ferrari AJ1, 9, 12
  15. Fitzmaurice C1
  16. Foreman K1
  17. Forouzanfar MH1
  18. Fullman N1
  19. Goldberg EM1
  20. Graetz N1
  21. Haagsma JA1, 19
  22. Hay SI1, 16
  23. Johnson CO1
  24. Kemmer L1
  25. Khalil IA1
  26. Kinfu Y1, 20
  27. Kutz MJ1
  28. Kyu HH1
  29. Leung J1, 9, 12
  30. Lim SS1
  31. Lozano R1
  32. Mikesell J1
  33. Mokdad AH1
  34. Mooney MD1
  35. Naghavi M1
  36. Nguyen G1
  37. Nsoesie E1
  38. Pigott DM1
  39. Pinho C1
  40. Rankin Z1
  41. Reinig N1
  42. Sandar L1
  43. Smith A1
  44. Sorensen RJD1
  45. Stanaway J1
  46. Steiner C1
  47. Teeple S1
  48. Thomas BA1
  49. Troeger C1
  50. Vanderzanden A1
  51. Wagner JA1
  52. Wanga V1
  53. Whiteford HA1, 9, 12
  54. Zhou M1, 21
  55. Zoeckler L1
  56. Achoki T1
  57. Afshin A1
  58. Alexander LT1
  59. Allen C1
  60. Anderson GM1
  61. Bell B1
  62. Bienhoff K1
  63. Biryukov S1
  64. Blore JD1
  65. Estep K1
  66. Friedman J1
  67. Frostad J1
  68. Godwin WW1
  69. Liu PY1
  70. Masiye F1, 188
  71. Millear A1
  72. Mirarefin M1
  73. Moradilakeh M1, 405
  74. Mumford JE1
  75. Ng M1
  76. Reitsma MB1
  77. Reynolds A1
  78. Roth GA1
  79. Sur PJ1
  80. Vollset SE1, 269, 347
  81. Vos T1
  82. Lopez AD1, 68
  83. Murray CJL1
  84. Ellenbogen RG2
  85. Mock CN3
  86. Anderson BO4
  87. Futran ND4
  88. Bhutta ZA5, 7
  89. Nisar MI6
  90. Akseer N7, 49
  91. Deveber GA8
  92. Abajobir AA9
  93. Knibbs LD9
  94. Lalloo R10
  95. Alam NKM11, 72
  96. Gouda HN11
  97. Guo Y11
  98. Mcgrath JJ11
  99. Jeemon P13, 306
  100. Dandona R14
  101. Kumar GA14
  102. Gething PW15
  103. Bisanzio D17
  104. Ali R18
  105. Bennett DA18
  106. Jha V18, 307
  107. Rahimi K18
  108. Duan L21
  109. Jin Y21
  110. Li Y21
  111. Wang L21
  112. Ye P21
  113. Liang X22
  114. Mensah GA23
  115. Salomon JA24
  116. Thornelyman AL25, 513
  117. Barnighausen T26, 125, 126
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  119. Ding EL26
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  121. Wagner GR26, 535
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  124. Ahmed MB28
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  250. Beyene AS146
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  253. Bhala N147, 148
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  255. Piel FB151
  256. Steiner TJ152, 494
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  258. Majeed A153
  259. Soljak M153
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  261. Bikbov B155
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  263. Bjertness E157
  264. Bourne RRA158
  265. Brainin M159
  266. Brazinova A160, 161
  267. Majdan M160
  268. Shen J162, 476
  269. Breitborde NJK163
  270. Brenner H164
  271. Brugha TS165
  272. Buckle GC167
  273. Butt ZA168
  274. Calabria B169, 173
  275. Lucas RM169
  276. Boufous S170
  277. Degenhardt L171
  278. Resnikoff S172
  279. Mitchell PB173
  280. Campuzano JC174
  281. Gomezdantes H174
  282. Herediapi IB174
  283. Jauregui A174
  284. Montanez Hernandez JC174
  285. Servanmori EE174
  286. Carabin H175
  287. Carapetis JR176
  288. Cardenas R177
  289. Castanedaorjuela CA178, 179
  290. Castillo Rivas J180, 181
  291. Catalalopez F182, 183
  292. Chang J184
  293. Chiang PP185
  294. Chibalabala M186
  295. Chibueze CE187
  296. Mori R187
  297. Chisumpa VH188, 189
  298. Choi JJ190
  299. Choudhury L191
  300. Christensen H192
  301. Colomar M194
  302. Crump JA195
  303. Derrett S196
  304. Poulton RG197
  305. Giussani G198
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  310. Dargan PI200
  311. Das Neves J201
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  314. Davey G204
  315. Davis AC205
  316. Newton JN205
  317. Steel N205, 491
  318. De Leo D206
  319. Des Jarlais DC207, 208
  320. Dharmaratne SD209
  321. Dhillon PK210
  322. Zodpey S210
  323. Doyle KE211
  324. Dubey M212
  325. Rahman MHU212
  326. Ram U212
  327. Singh A212
  328. Yadav AK212
  329. Duncan BB213, 214
  330. Kieling C213, 343
  331. Schmidt MI213
  332. Ebrahimi H215, 216
  333. Esteghamati A215
  334. Farzadfar F215
  335. Hafezinejad N215
  336. Kasaeian A215, 220
  337. Parsaeian M215, 221
  338. Pishgar F215, 222
  339. Sheikhbahaei S215
  340. Fahimi S217
  341. Malekzadeh R217
  342. Roshandel G217, 463
  343. Sepanlou SG217
  344. Hassanvand MS218
  345. Heydarpour P219
  346. Rahimimovaghar V223
  347. Elyazar I225
  348. Endries AY226
  349. Ermakov SP227, 228
  350. Eshrati B229, 230
  351. Farid TA231
  352. Khan AR231
  353. Farinha CSES232, 233
  354. Faro A234
  355. Feigin VL236
  356. Te BJ237
  357. Fernandes JG238
  358. Fernandes JC239
  359. Fischer F240
  360. Foigt N241
  361. Fowkes FGR242
  362. Franklin RC243
  363. Garciabasteiro AL245, 246
  364. Geleijnse JM248
  365. Jibat T249, 255
  366. Gibney KB250
  367. Gillum RF252
  368. Mehari A252
  369. Ginawi IA253
  370. Hailu AD132, 254, 270
  371. Giref AZ255
  372. Haile D255
  373. Giroud M256
  374. Gishu MD257, 258
  375. Tura AK257, 286
  376. Gona P259
  377. Goodridge A260
  378. Gopalani SV261
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  384. Inoue M264, 300
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  397. Hankey GJ277, 278, 279
  398. Harikrishnan S280
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  400. Hedayati MT284
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  411. Idrisov BT297
  412. Kwan GF137
  413. Innos K298, 299
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Source: The Lancet Published:2016


Abstract

Background Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. Methods We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. Findings Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9–3·0) for men and 3·5 years (3·4–3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78–0·92) and 1·2 years (1·1–1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. Interpretation Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license
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