Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16
India accounts for approximately one third of the world's total population of stunted preschoolers. Addressing global undernutrition, therefore, requires an understanding of the determinants of stunting across India's diverse states and districts. We created a district‐level aggregate data set from...
| Autores principales: | , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2018
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/146031 |
| _version_ | 1855523333625348096 |
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| author | Menon, Purnima Headey, Derek D. Avula, Rasmi Nguyen, Phuong Hong |
| author_browse | Avula, Rasmi Headey, Derek D. Menon, Purnima Nguyen, Phuong Hong |
| author_facet | Menon, Purnima Headey, Derek D. Avula, Rasmi Nguyen, Phuong Hong |
| author_sort | Menon, Purnima |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | India accounts for approximately one third of the world's total population of stunted preschoolers. Addressing global undernutrition, therefore, requires an understanding of the determinants of stunting across India's diverse states and districts. We created a district‐level aggregate data set from the recently released 2015–2016 National and Family Health Survey, which covered 601,509 households in 640 districts. We used mapping and descriptive analyses to understand spatial differences in distribution of stunting. We then used population‐weighted regressions to identify stunting determinants and regression‐based decompositions to explain differences between high‐and low‐stunting districts across India. |
| format | Journal Article |
| id | CGSpace146031 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1460312025-12-08T10:29:22Z Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 Menon, Purnima Headey, Derek D. Avula, Rasmi Nguyen, Phuong Hong child nutrition stunting malnutrition nutrition spatial analysis India accounts for approximately one third of the world's total population of stunted preschoolers. Addressing global undernutrition, therefore, requires an understanding of the determinants of stunting across India's diverse states and districts. We created a district‐level aggregate data set from the recently released 2015–2016 National and Family Health Survey, which covered 601,509 households in 640 districts. We used mapping and descriptive analyses to understand spatial differences in distribution of stunting. We then used population‐weighted regressions to identify stunting determinants and regression‐based decompositions to explain differences between high‐and low‐stunting districts across India. 2018-06-19 2024-06-21T09:05:38Z 2024-06-21T09:05:38Z Journal Article https://hdl.handle.net/10568/146031 en Open Access Wiley Menon, Purnima; Headey, Derek D.; Avula, Rasmi; and Nguyen, Phuong Hong. 2018. Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16. Maternal and Child Nutrition 14(4): e12620. https://doi.org/10.1111/mcn.12620 |
| spellingShingle | child nutrition stunting malnutrition nutrition spatial analysis Menon, Purnima Headey, Derek D. Avula, Rasmi Nguyen, Phuong Hong Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title | Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title_full | Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title_fullStr | Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title_full_unstemmed | Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title_short | Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16 |
| title_sort | understanding the geographical burden of stunting in india a regression decomposition analysis of district level data from 2015 16 |
| topic | child nutrition stunting malnutrition nutrition spatial analysis |
| url | https://hdl.handle.net/10568/146031 |
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