2020
DOI: 10.1016/j.eclinm.2020.100317
|View full text |Cite
|
Sign up to set email alerts
|

Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Abstract: Background: To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states. Methods: We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 £ 5 km grid estimates, using all accessible data from various surveys with subnational geographical information.… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
21
0
1

Year Published

2020
2020
2023
2023

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 31 publications
(24 citation statements)
references
References 45 publications
2
21
0
1
Order By: Relevance
“…Thus, our findings suggest that the decision about which geographic unit health interventions should be targeted at depends on the state and the risk factor. Finally, findings from previous studies show that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh are among the worst performing Indian states in terms of child malnutrition outcomes (Hemalatha et al, 2020;Swaminathan et al, 2019). Our findings show that each of these were the only states in the highest risk quintile for more than 10 of the 21 risk factors for child undernutrition.…”
Section: T a B L E 1 Geographic Hierarchy And Distribution Of Risk Factors Included In Analysissupporting
confidence: 53%
“…Thus, our findings suggest that the decision about which geographic unit health interventions should be targeted at depends on the state and the risk factor. Finally, findings from previous studies show that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh are among the worst performing Indian states in terms of child malnutrition outcomes (Hemalatha et al, 2020;Swaminathan et al, 2019). Our findings show that each of these were the only states in the highest risk quintile for more than 10 of the 21 risk factors for child undernutrition.…”
Section: T a B L E 1 Geographic Hierarchy And Distribution Of Risk Factors Included In Analysissupporting
confidence: 53%
“…The use of multiple modeling techniques allows any complex non-linear effects of the covariates to be captured, while the final predictions are estimated using a robust, consolidated modeling technique. All 11 studies following this approach [27][28][29][30][31][32][33][34][35][36][37] used a Bayesian hierarchical model fitted using INLA for the final predictions. Only one study relied on ensemble models and did not perform stacked generalization [38].…”
Section: Modeling Techniquesmentioning
confidence: 99%
“…The burden of stunting, wasting, underweight and overweight was estimated for the entire African continent [28] and in all LMICs [27,37]. There were also several single country studies that account for and focus on local specificities as done in Bangladesh [98], Afghanistan [99], Cambodia [100], India [36], Mexico [101] and Ethiopia [24,102]. Five studies generated estimates at district or province level [98][99][100]102], four studies at 1x1km [45], 5x5km [27,28] and 10x10km [103], and two studies at both 5x5km and administrative level [36,37].…”
Section: Malnutritionmentioning
confidence: 99%
“…The prevalence of stunting, wasting and underweight reportedly were 38 %, 21 % and 36 %, respectively, in 2015-2016 (9) . Undernutrition is unacceptably higher in many states, with stark and vast differences between and within states and by population groups in India (9)(10)(11)(12) .…”
mentioning
confidence: 99%