Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Mapping Child Growth Failure Across Low- and Middle-Income Countries Publisher Pubmed



Kinyoki DK1, 304 ; Osgoodzimmerman AE304 ; Pickering BV304 ; Schaeffer LE304 ; Marczak LB304 ; Lazzaratwood A304 ; Collison ML304 ; Henry NJ304 ; Abebe Z2 ; Adamu AA3, 4 ; Adekanmbi V5 ; Ahmadi K6 ; Ajumobi O7, 8 ; Aleyadhy A9 Show All Authors
Authors
  1. Kinyoki DK1, 304
  2. Osgoodzimmerman AE304
  3. Pickering BV304
  4. Schaeffer LE304
  5. Marczak LB304
  6. Lazzaratwood A304
  7. Collison ML304
  8. Henry NJ304
  9. Abebe Z2
  10. Adamu AA3, 4
  11. Adekanmbi V5
  12. Ahmadi K6
  13. Ajumobi O7, 8
  14. Aleyadhy A9
  15. Alraddadi RM10
  16. Alahdab F11
  17. Alijanzadeh M12
  18. Alipour V13, 14
  19. Altirkawi K15
  20. Amini S16
  21. Andrei CL17
  22. Antonio CAT18, 19
  23. Arabloo J14
  24. Aremu O20
  25. Asadialiabadi M21
  26. Atique S22
  27. Ausloos M23, 24, 111
  28. Avila M25
  29. Awasthi A26, 27
  30. Quintanilla BPA28, 29
  31. Azari S14
  32. Badawi A30, 31
  33. Barnighausen TW32, 33
  34. Bassat Q34, 35
  35. Baye K36
  36. Bedi N37, 38
  37. Bekele BB39, 40
  38. Bell ML41
  39. Bhattacharjee NV304
  40. Bhattacharyya K42, 43
  41. Bhattarai S44
  42. Bhutta ZA45, 46
  43. Biadgo B47
  44. Bikbov B48
  45. Briko AN49
  46. Britton G50
  47. Burstein R304
  48. Butt ZA51, 52
  49. Car J53, 54
  50. Castanedaorjuela CA55, 56
  51. Castro F57
  52. Cerin E58, 59
  53. Chipeta MG60
  54. Chu DT61
  55. Cork MA304
  56. Cromwell EA1, 304
  57. Cuevasnasu L25
  58. Dandona L27, 304
  59. Dandona R27, 304
  60. Daoud F304
  61. Gupta RD62, 63
  62. Weaver ND304
  63. Leo DD64
  64. Neve JWD32
  65. Deribe K65, 66
  66. Desalegn BB67
  67. Deshpande A304
  68. Desta M68, 69
  69. Diaz D69, 70
  70. Dinberu MT71
  71. Doku DT72, 73
  72. Dubey M74
  73. Duraes AR75, 76
  74. Dwyerlindgren L1, 304
  75. Earl L304
  76. Effiong A77
  77. Zaki MES78
  78. Tantawi ME79
  79. Elkhatib Z80, 81
  80. Eshrati B82, 83
  81. Fareed M84
  82. Faro A85
  83. Fereshtehnejad SM86, 87
  84. Filip I88, 89
  85. Fischer F90
  86. Foigt NA91
  87. Folayan MO92
  88. Fukumoto T93, 94
  89. Gebrehiwot TT95
  90. Gezae KE96
  91. Ghajar A97, 98
  92. Gill PS99
  93. Gona PN100
  94. Gopalani SV101, 102
  95. Grada A103
  96. Guo Y104, 105
  97. Hajmirzaian A106, 107
  98. Hajmirzaian A106, 107
  99. Hall JB304
  100. Hamidi S109
  101. Henok A40
  102. Prado BH1, 304
  103. Herrero M110
  104. Herteliu C24, 111
  105. Hoang CL112
  106. Hole MK113
  107. Hossain N114, 115
  108. Hosseinzadeh M116, 117
  109. Hu G118
  110. Islam SMS119, 120
  111. Jakovljevic M121
  112. Jha RP122
  113. Jonas JB123, 124
  114. Jozwiak JJ125
  115. Kahsay A126
  116. Kanchan T127
  117. Karami M128
  118. Kasaeian A129, 130
  119. Khader YS131
  120. Khan EA132
  121. Khater MM133
  122. Kim YJ134
  123. Kimokoti RW135
  124. Kisa A136
  125. Kochhar S137, 138
  126. Kosen S139
  127. Koyanagi A35, 140
  128. Krishan K141
  129. Defo BK142, 143
  130. Kumar GA27
  131. Kumar M144, 145
  132. Lad SD146
  133. Lami FH147
  134. Lee PH148
  135. Levine AJ304
  136. Li S104
  137. Linn S149
  138. Lodha R150
  139. El Razek HMA151
  140. Abd El Razek MM152
  141. Majdan M153
  142. Majeed A154
  143. Malekzadeh R155, 156
  144. Malta DC157
  145. Mamun AA158
  146. Mansournia MA159
  147. Martinsmelo FR160
  148. Masaka A161
  149. Massenburg BB162
  150. Mayala BK304
  151. Mejiarodriguez F163
  152. Melku M39
  153. Mendoza W164
  154. Mensah GA165, 166
  155. Miazgowski T167
  156. Miller TR168, 169
  157. Mini GK170, 171
  158. Mirrakhimov EM172, 173
  159. Moazen B32, 174
  160. Darwesh AM175
  161. Mohammed S32, 176
  162. Mohebi F177
  163. Mokdad AH1, 304
  164. Moodley Y178
  165. Moradi G179, 180
  166. Moradilakeh M21
  167. Moraga P181
  168. Morrison SD182
  169. Mosser JF304
  170. Mousavi SM183, 184
  171. Mueller UO185, 186
  172. Murray CJL1, 304
  173. Mustafa G187, 188
  174. Naderi M189
  175. Naghavi M1, 304
  176. Najafi F190
  177. Nangia V191
  178. Ndwandwe DE4
  179. Negoi I192
  180. Ngunjiri JW193
  181. Nguyen HLT194
  182. Nguyen LH112
  183. Nguyen SH112
  184. Nie J195
  185. Nnaji CA4, 196
  186. Noubiap JJ166
  187. Shiadeh MN197
  188. Nyasulu PS198
  189. Ogbo FA199
  190. Olagunju AT200, 201
  191. Olusanya BO202
  192. Olusanya JO202
  193. Ortizpanozo E203, 204
  194. Otstavnov SS205, 206
  195. P A M207
  196. Pana A24, 111, 208
  197. Pandey A27
  198. Pati S209
  199. Patil ST210
  200. Patton GC211, 212
  201. Perico N213
  202. Pigott DM1, 304
  203. Pirsaheb M214
  204. Piwoz EG215
  205. Postma MJ216, 217
  206. Pourshams A155
  207. Prakash S218
  208. Quintana H57
  209. Radfar A219, 220
  210. Rafiei A221, 222
  211. Rahimimovaghar V223
  212. Rai RK224, 225
  213. Rajati F214
  214. Rawaf DL226, 227
  215. Rawaf S228, 229
  216. Rawat R215
  217. Remuzzi G213
  218. Renzaho AMN230, 231
  219. Riosgonzalez C232, 233
  220. Roever L234
  221. Ross JM137, 304
  222. Rostami A235
  223. Sadat N304
  224. Safari Y214
  225. Safdarian M223, 236
  226. Sahebkar A237, 238
  227. Salam N239
  228. Salamati P223
  229. Salimi Y190, 240
  230. Salimzadeh H155
  231. Samy AM241
  232. Sartorius B1, 242
  233. Sathian B243, 244
  234. Schipp MF304
  235. Schwebel DC245
  236. Senbeta AM246
  237. Sepanlou SG155, 156
  238. Shaikh MA247
  239. Levy TS25
  240. Shamsi M248
  241. Sharafi K214
  242. Sharma R249
  243. Sheikh A250, 251
  244. Shil A252
  245. Silva DAS253
  246. Singh JA254, 255
  247. Sinha DN256, 257
  248. Soofi M240
  249. Sudaryanto A258, 259
  250. Sufiyan MB260
  251. Tabaresseisdedos R261, 262
  252. Tadesse BT263, 264, 266
  253. Temsah MH265, 266
  254. Terkawi AS267, 268
  255. Tessema ZT269
  256. Thornelyman AL270
  257. Tovanipalone MR271
  258. Tran BX272
  259. Tran KB273, 274
  260. Ullah I275, 276
  261. Uthman OA277
  262. Vaezghasemi M278
  263. Vaezi A279
  264. Valdez PR280, 281
  265. Vanderheide J304
  266. Veisani Y282
  267. Violante FS283, 284
  268. Vlassov V285
  269. Vu GT112
  270. Vu LG112
  271. Waheed Y286
  272. Walson JL137
  273. Wang Y287
  274. Wang YP288
  275. Wangia EN289
  276. Werdecker A185, 186
  277. Xu G290
  278. Yamada T291
  279. Yisma E292
  280. Yonemoto N293
  281. Younis MZ294, 295
  282. Yousefifard M296
  283. Yu C287, 297
  284. Zaman SB298, 299
  285. Zamani M300
  286. Zhang Y301, 302
  287. Kassebaum NJ303, 304
  288. Hay SI1, 304

Source: Nature Published:2020


Abstract

Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0–59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3–5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization’s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99% of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications. © 2020, The Author(s).
Other Related Docs