TY - JOUR
T1 - Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17
T2 - Analysis for the Global Burden of Disease Study 2017
AU - Local Burden of Disease Diarrhoea Collaborators
AU - Reiner, Robert C.
AU - Wiens, Kirsten E.
AU - Deshpande, Aniruddha
AU - Baumann, Mathew M.
AU - Lindstedt, Paulina A.
AU - Blacker, Brigette F.
AU - Troeger, Christopher E.
AU - Earl, Lucas
AU - Munro, Sandra B.
AU - Abate, Degu
AU - Abbastabar, Hedayat
AU - Abd-Allah, Foad
AU - Abdelalim, Ahmed
AU - Abdollahpour, Ibrahim
AU - Abdulkader, Rizwan Suliankatchi
AU - Abebe, Getaneh
AU - Abegaz, Kedir Hussein
AU - Abreu, Lucas Guimarães
AU - Abrigo, Michael R.M.
AU - Accrombessi, Manfred Mario Kokou
AU - Acharya, Dilaram
AU - Adabi, Maryam
AU - Adebayo, Oladimeji M.
AU - Adedoyin, Rufus Adesoji
AU - Adekanmbi, Victor
AU - Adetokunboh, Olatunji O.
AU - Adham, Davoud
AU - Adhena, Beyene Meressa
AU - Afarideh, Mohsen
AU - Ahmadi, Keivan
AU - Ahmadi, Mehdi
AU - Ahmed, Anwar E.
AU - Ahmed, Muktar Beshir
AU - Ahmed, Rushdia
AU - Ajumobi, Olufemi
AU - Akal, Chalachew Genet
AU - Akalu, Temesgen Yihunie
AU - Akanda, Ali S.
AU - Alamene, Genet Melak
AU - Alanzi, Turki M.
AU - Albright, James R.
AU - Alcalde Rabanal, Jacqueline Elizabeth
AU - Alemnew, Birhan Tamene
AU - Alemu, Zewdie Aderaw
AU - Ali, Beriwan Abdulqadir
AU - Ali, Muhammad
AU - Alijanzadeh, Mehran
AU - Alipour, Vahid
AU - Aljunid, Syed Mohamed
AU - Linn, Shai
N1 - Publisher Copyright:
© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
PY - 2020/6/6
Y1 - 2020/6/6
N2 - Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health.
AB - Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health.
KW - Bayes Theorem
KW - Child, Preschool
KW - Developing Countries/statistics & numerical data
KW - Diarrhea/epidemiology
KW - Global Burden of Disease/statistics & numerical data
KW - Global Health/statistics & numerical data
KW - Healthcare Disparities/statistics & numerical data
KW - Humans
KW - Incidence
KW - Prevalence
UR - http://www.scopus.com/inward/record.url?scp=85086298953&partnerID=8YFLogxK
U2 - 10.1016/S0140-6736(20)30114-8
DO - 10.1016/S0140-6736(20)30114-8
M3 - Article
C2 - 32513411
AN - SCOPUS:85086298953
SN - 0140-6736
VL - 395
SP - 1779
EP - 1801
JO - The Lancet
JF - The Lancet
IS - 10239
ER -