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Identifying Geographical Heterogeneity in Associations between Under-Five Child Nutritional Status and Its Correlates Across Indian Districts

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Abstract

India has substantially reduced the burden of under-five child malnutrition over the last two decades. Despite this, it is still gigantic and differs remarkably across districts, while the demographic and socio-economic groups are most affected by it. This paper aimed to decrypt the place-specific spatial dependence and heterogeneity in associations between district-level nutritional status (stunting, wasting and underweight) and its considered correlates using a geocoded database for all 640 Indian districts from the latest fourth wave of the National Family Health Survey, 2015–16. Univariate Moran’s I and LISA statistics were used to confirm the spatial clustering and dependence in under-five nutritional status. The Ordinary Least Square (OLS), Geographically Weighted Regression (GWR), Spatial (lag/error) models were employed to examine the effects of correlates on the district-level nutritional status. The mean (Moran’s I) district-level stunting, wasting and underweight were 38% (0.634), 21% (0.488) and 36% (0.721), respectively. The GWR results disclosed that the spatial heterogeneity in relationships between district-level nutritional status and its driving forces were strongly location-based, altering their direction, magnitude and strength across districts. Overall, the localized model performed better, and best fit the data than the OLS and spatial (lag/error) models. This nationwide study confirmed that the spatial dependencies and heterogeneities in the district-level nutritional status indicators were strongly explained by a multitude of factors and thus can help policymakers in formulating effective nutrition-specific programmatic interventions to speed up the coverage of under-five malnutrition status in most priority districts and geographical hot spots across India.

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Fig. 1

Source: Estimated by author from the NFHS, 2017

Fig. 2

Data Source: Estimated by author from the NFHS, 2017

Fig. 3

Source: Estimated by author from the NFHS, 2017

Fig. 4

Source: Estimated by author from the NFHS, 2017

Fig. 5

Source: Estimated by author from the NFHS, 2017

Fig. 6

Source: Estimated by author from the NFHS, 2017

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Availability of Data and Material

The National Family Health Survey-4 data is available in the public domain from the DHS data repository and could be accessed upon request through https://www.dhsprogram.com/data/dataset_admin.

Code Availability

The data that support the findings of this study is available from the corresponding author, upon reasonable request.

References

  • Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.

    Article  Google Scholar 

  • Anselin, L. (2001). Spatial econometric. In B. Baltagi (Ed). Companion to econometrics (pp. 310–330). Wiley.

  • Anselin, L. (2010). Thirty years of spatial econometrics. Papers in Regional Science, 89(1), 3–25.

    Article  Google Scholar 

  • Anselin, L., & Rey, S. (1991). Properties of tests for spatial dependence in linear regression models. Geographical Analysis, 23(2), 112–131.

    Article  Google Scholar 

  • Anselin, L., Syabri, I., & Kho, Y. (2010). GeoDa: An introduction to spatial data analysis. In M. M. Fischer & A. Getis (Eds.), Handbook of applied spatial analysis (pp. 73–89). Springer.

  • Bawdekar, M., & Ladusingh, L. (2008). Contextual correlates of child malnutrition in rural Maharashtra. Journal of Biosocial Science, 40(5), 771.

    Article  Google Scholar 

  • Bharti, R., Dhillon, P., & Narzary, P. K. (2019). A spatial analysis of childhood stunting and its contextual correlates in India. Clinical Epidemiology and Global Health, 7(3), 488–495.

    Article  Google Scholar 

  • Black, R. E., Victora, C. G., Walker, S. P., Bhutta, Z.A., Christian, P., De Onis, M., Ezzati, M., Grantham-McGregor, S., Katz, J., Martorell, R., Uauy, R., & the Maternal and Child Nutrition Study Group. (2013). Maternal and child undernutrition and overweight in low-income and middle-income countries. The Lancet, 382(9890), 427-451.

  • Caulfield, L. E., de Onis, M., Blössner, M., & Black, R. E. (2004). Undernutrition as an underlying cause of child deaths associated with diarrhea, pneumonia, malaria, and measles. The American Journal of Clinical Nutrition, 80(1), 193–198.

    Article  Google Scholar 

  • Checkley, W., Buckley, G., Gilman, R. H., Assis, A. M., Guerrant, R. L., Morris, S. S., Mølbak, K., Valentiner-Branth, P., Lanata, C. F., Black, R. E., Malnutrition, T. C., & Network, I. (2008). Multi-country analysis of the effects of diarrhoea on childhood stunting. International Journal of Epidemiology, 37(4), 816–830.

    Article  Google Scholar 

  • Chi, G. & Wang, D. (2017). Small-area population forecasting: A geographically weighted regression approach. In: D. A. Swanson (Ed) The frontiers of applied demography (pp. 449–471). Applied Demography Series, 9.

  • Clark, P. J., & Evans, F. C. (1954). Distance to nearest neighbour as a measure of spatial relationships in populations. Ecology, 35(4), 445–453.

    Article  Google Scholar 

  • Cliff, A. D., & Ord, J. K. (1981). Spatial processes: Models & applications. Taylor and Francis.

    Google Scholar 

  • Corsi, D. J., Mejía-Guevara, I., & Subramanian, S. V. (2016). Improving household-level nutrition-specific and nutrition-sensitive conditions key to reducing child undernutrition in India. Social Science and Medicine, 157, 189–192.

    Article  Google Scholar 

  • Cunha, A. L. (2000). Relationship between acute respiratory infection and malnutrition in children under 5 years of age. Acta Paediatrica, 89(5), 608–609.

    Article  Google Scholar 

  • Dasgupta, S., Ramaswamy, D. T. V., Noronha, K. M., Rao, S., George, N., Singh, A., ... & Bhol, A. (2016). Swachh Bharat: Industry engagement-scope & examples. Kimberly M. and Rao, Smitha and R., Seetharaman and George, Nikhil and Singh, Amandeep and Singh, Tripti and Dhiman, Swati and Bhol, Aditya, Swachh Bharat: Industry Engagement-Scope & Examples (January 22, 2016).

  • Debes, A. K., Kohli, A., Walker, N., Edmond, K., & Mullany, L. C. (2013). Time to initiation of breastfeeding and neonatal mortality and morbidity: A systematic review. BMC Public Health, 13(3), 1–14.

    Google Scholar 

  • Dewey, K. G., & Begum, K. (2011). Long-term consequences of stunting in early life. Maternal and Child Nutrition, 7, 5–18.

    Article  Google Scholar 

  • Di Cesare, M., Bhatti, Z., Soofi, S. B., Fortunato, L., Ezzati, M., & Bhutta, Z. A. (2015). Geographical and socioeconomic inequalities in women and children’s nutritional status in Pakistan in 2011: An analysis of data from a nationally representative survey. The Lancet Global Health, 3(4), e229–e239.

    Article  Google Scholar 

  • Fenske N., Burns J., Hothorn T., & Rehfuess E. A. (2013). Understanding child stunting in India: A comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression. PLoS ONE, 8(11).

  • Fink, G., Günther, I., & Hill, K. (2011). The effect of water and sanitation on child health: Evidence from the demographic and health surveys 1986–2007. International Journal of Epidemiology, 40(5), 1196–1204.

    Article  Google Scholar 

  • Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2003). Geographically weighted regression: The analysis of spatially varying relationship. Wiley.

    Google Scholar 

  • Frost, M. B., Forste, R., & Haas, D. W. (2005). Maternal education and child nutritional status in Bolivia: Finding the links. Social Science and Medicine, 60(2), 395–407.

    Article  Google Scholar 

  • Galasso, E., Wagstaff, A., Naudeau, S., & Shekar, M. (2016). The economic costs of stunting and how to reduce them. Policy Research Note World Bank.

    Google Scholar 

  • Getis, A. & ORD, J. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206.

  • Ghosh, S., Sharma, S. K., & Bhattacharya, D. (2020). Deciphering disparities in childhood stunting in an underdeveloped state of India: An investigation applying the unconditional quantile regression method. BMC Public Health, 20(1), 1–21.

    Article  Google Scholar 

  • Gillespie, S. & Haddad, L. (2003). The double burden of malnutrition in Asia: Causes, consequences, and solutions. Sage Publications India.

  • Global Hunger Index (GHI). (2020). Global, regional, and national trends - global hunger index - peer-reviewed annual publication designed to comprehensively measure and track hunger at the global, regional, and country levels. Global Hunger Index.

  • Gupta, A. K., & Santhya, K. G. (2020). Proximal and contextual correlates of childhood stunting in India: A geo-spatial analysis. PLoS ONE, 15(8), e0237661.

    Article  Google Scholar 

  • Haile, D., Azage, M., Mola, T., & Rainey, R. (2016). Exploring spatial variations and factors associated with childhood stunting in Ethiopia: Spatial and multilevel analysis. BMC Pediatrics, 16(1), 1–14.

    Article  Google Scholar 

  • IIPS & ICF. (2017). National Family Health Survey (NFHS-4), 2015–16: India. Mumbai: International Institute for Population Sciences.

  • IIPS & Macro International. (1995). National Family Health Survey (NFHS-1), 1992-93: India. Mumbai: International Institute for Population Sciences.

  • International Food Policy Research Institute (IFPRI) (2014). Global nutrition report, actions and accountability to accelerate the world's progress on nutrition. Washington, DC.

  • Ishizawa, H., & Stevens, G. (2007). Non-English language neighbourhoods in Chicago, Illinois: 2000. Social Science Research, 36(3), 1042–1064.

    Article  Google Scholar 

  • Jenks, G. F., & Caspall, F. C. (1971). Error on choroplethic maps: Definition, measurement, reduction. Annals of the Association of American Geographers, 61(2), 217–244.

    Article  Google Scholar 

  • Jose, S., Bheemeshwar Reddy, A., & Agrawal, M. (2018). Child undernutrition in India. Economic and Political Weekly, 54(49), 15.

    Google Scholar 

  • Jun, H. J. (2017). The spatial dynamics of neighbourhood change: Exploring spatial dependence in neighbourhood housing value change. Housing Studies, 32(6), 717–741.

    Article  Google Scholar 

  • Kanjilal, B., Mazumdar, P. G., Mukherjee, M., & Rahman, M. H. (2010). Nutritional status of children in India: Household socio-economic condition as the contextual determinant. International Journal for Equity in Health, 9(1), 1–13.

    Article  Google Scholar 

  • Khan, J., & Mohanty, S. K. (2018). Spatial heterogeneity and correlates of child malnutrition in districts of India. BMC Public Health, 18(1), 1–13.

    Article  Google Scholar 

  • Kravdal, Ø. (2004). Child mortality in India: The community-level effect of education. Population Studies, 58(2), 177–192.

    Article  Google Scholar 

  • Liu, L., Oza, S., Hogan, D., Chu, Y., Perin, J., Zhu, J., Lawn, J. E., Cousens, S., Mathers, C., & Black, R. E. (2016). Global, regional, and national causes of under-5 mortality in 2000–2015: An updated systematic analysis with implications for the Sustainable Development Goals. The Lancet, 388(10063), 3027–3035.

    Article  Google Scholar 

  • Lloyd, C. D. (2010). Local models for spatial analysis. Taylor & Francis.

    Book  Google Scholar 

  • Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T., & Murray, C. J. (2006). Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. The Lancet, 367(9524), 1747–1757.

    Article  Google Scholar 

  • Malavika, A., Subramanyam, M. A., Kawachi, I., Berkman, L. F., & Subramanian, S. V. (2011). Is economic growth associated with reduction in child undernutrition in India? PLoS Medicine, 8(3), e1000424.

    Article  Google Scholar 

  • Martorell, R. (1992). Long-term consequences of growth retardation during early childhood. In M. Hernandez & J. Argente (Eds.), Human growth: Basic and clinical aspects (pp. 143–149). Excerpta Medica.

  • Martorell, R., & Young, M. F. (2012). Patterns of stunting and wasting: Potential explanatory factors. Advances in Nutrition, 3(2), 227–233.

    Article  Google Scholar 

  • Martorell, R., & Zongrone, A. (2012). Intergenerational influences on child growth and undernutrition. Paediatric and Perinatal Qpidemiology, 26, 302–314.

    Article  Google Scholar 

  • Masoud, S., Menon, P., & Bhutta, Z. A. (2018). Addressing child malnutrition in India. In V. R. Preedy & V. B. Patel (Eds.), Handbook of famine, starvation, and nutrient deprivation: From biology to policy (pp. 1–16). Springer.

  • McDonald, C. M., Olofin, I., Flaxman, S., Fawzi, W. W., Spiegelman, D., Caulfield, L. E., & Nutrition Impact Model Study. (2013). The effect of multiple anthropometric deficits on child mortality: Meta-analysis of individual data in 10 prospective studies from developing countries. The American Journal of Clinical Nutrition, 97(4), 896-901.

  • Mejía-Guevara, I., Krishna, A., Corsi, D. J., & Subramanian, S. V. (2015). Individual and ecological variation in child undernutrition in India: A multilevel analysis. Journal of South Asian Development, 10(2), 168–198.

    Article  Google Scholar 

  • Menon, P., Headey, D., Avula, R., & Nguyen, P. H. (2018). Understanding the geographical burden of stunting in India: A regression-decomposition analysis of district-level data from 2015 to 2016. Maternal & Child Nutrition, 14(4), e12620.

    Article  Google Scholar 

  • Mishra, V. K., & Retherford, R. D. (2000). Women's education can improve child nutrition in India. Prime.

  • Murray, S. F., Hunter, B. M., Bisht, R., Ensor, T., & Bick, D. (2014). Effects of demand-side financing on utilisation, experiences and outcomes of maternity care in low-and middle-income countries: A systematic review. BMC Pregnancy and Childbirth, 14(1), 1–15.

    Article  Google Scholar 

  • Nakaya, T. (2015). Semiparametric geographically weighted generalised linear modelling: The concept and implementation using GWR4. In C. Brunsdon & A. Singleton (Eds), Geocomputation: A practical primer (pp. 201–220). Sage.

    Google Scholar 

  • Nandy, S., Irving, M., Gordon, D., Subramanian, S. V., & Smith, G. D. (2005). Poverty, child undernutrition and morbidity: New evidence from India. Bulletin of the World Health Organization, 83, 210–216.

    Google Scholar 

  • Nie, P., Rammohan, A., Gwozdz, W., & Sousa-Poza, A. (2019). Changes in child nutrition in India: A decomposition approach. International Journal of Environmental Research and Public Health, 16(10), 1815.

    Article  Google Scholar 

  • Páez, A., Uchida, T., & Miyamoto, K. (2002). A general framework for estimation and inference of geographically weighted regression models: 1. Location-specific kernel bandwidths and a test for locational heterogeneity. Environment and Planning A, 34(4), 733–754.https://doi.org/10.1068/a34110

    Article  Google Scholar 

  • Pathak, P. K. (2009). Socioeconomic inequality in malnutrition in India, 1992–2005. Paper to be presented at the annual meeting of Population Association of America (PAA) at Detroit, Michigan, USA, April 29-May (Vol. 2).

  • Pelletier, D. L., Frongillo, E. A., Jr., Schroeder, D. G., & Habicht, J. P. (1994). A methodology for estimating the contribution of malnutrition to child mortality in developing countries. The Journal of Nutrition, 124(10), 2106S-2122S.

    Google Scholar 

  • Pickett, K. E., & Wilkinson, R. G. (2015). Income inequality and health: A causal review. Social Science and Medicine, 128, 316–326.

    Article  Google Scholar 

  • Press Information Bureau (2017). Cabinet approves setting up of National Nutrition Mission (NNM) 2018. New Delhi: Press Information Bureau, Government of India. Available from: http://pib.nic.in/newsite/PrintRelease.aspx?relid=174025. Accessed 10th December 2019.

  • Puri, P., Khan, J., Shil, A., & Ali, M. (2020). A cross-sectional study on selected child health outcomes in India: Quantifying the spatial variations and identification of the parental risk factors. Scientific Reports, 10(1), 1–15.

    Article  Google Scholar 

  • Rah, J. H., Cronin, A. A., Badgaiyan, B., Aguayo, V. M., Coates, S., & Ahmed, S. (2015). Household sanitation and personal hygiene practices are associated with child stunting in rural India: A cross-sectional analysis of surveys. BMJ Open, 5(2).

  • Rice, A. L., Sacco, L., Hyder, A., & Black, R. E. (2000). Malnutrition as an underlying cause of childhood deaths associated with infectious diseases in developing countries. Bulletin of the World Health Organization, 78, 1207–1221.

    Google Scholar 

  • Ruel, M. T., & Menon, P. (2002). Child feeding practices are associated with child nutritional status in Latin America: Innovative uses of the demographic and health surveys. The Journal of Nutrition, 132(6), 1180–1187.

    Article  Google Scholar 

  • Rutstein, S. O. (2015). Steps to constructing the new DHS Wealth Index. ICF International.

  • Samir, K. C., Wurzer, M., Speringer, M., & Lutz, W. (2018). Future population and human capital in heterogeneous India. Proceedings of the National Academy of Sciences, 115(33), 8328–8333.

    Article  Google Scholar 

  • Sánchez, A. (2017). The structural relationship between early nutrition, cognitive skills and non-cognitive skills in four developing countries. Economics & Human Biology, 27, 33–54.

    Article  Google Scholar 

  • Sarkar, R., Sivarathinaswamy, P., Thangaraj, B., Sindhu, K. N. C., Ajjampur, S. S. R., Muliyil, J., Balraj, V., Naumova, E. N., Ward, H., & Kang, G. (2013). Burden of childhood diseases and malnutrition in a semi-urban slum in southern India. BMC Public Health, 13(1), 1–14.

    Article  Google Scholar 

  • Semba, R. D., de Pee, S., Sun, K., Sari, M., Akhter, N., & Bloem, M. W. (2008). Effect of parental formal education on risk of child stunting in Indonesia and Bangladesh: A cross-sectional study. The Lancet, 371(9609), 322–328.

    Article  Google Scholar 

  • Sheet, I. F. (2017). National Family Health Survey-4 (NFHS-4). International Institute for Population Studies.

  • Singh, A., Pathak, P. K., Chauhan, R. K., & Pan, W. (2011). Infant and child mortality in India in the last two decades: A geospatial analysis. PLoS ONE, 6, e26856.

    Article  Google Scholar 

  • Spears, D., Ghosh, A., & Cumming, O. (2013). Open defecation and childhood stunting in India: An ecological analysis of new data from 112 districts. PLoS ONE, 8(9), e73784.

    Article  Google Scholar 

  • Srivastava, S., Chandra, H., Singh, S. K., & Upadhyay, A. K. (2021). Mapping changes in district level prevalence of childhood stunting in India1998–2016: An application of small area estimation techniques. SSM-Population Health, 100748.

  • Striessnig, E., & Bora, J. K. (2020). Under-five child growth and nutrition status: Spatial clustering of Indian districts. Spatial Demography, 8(1), 63–84.

    Article  Google Scholar 

  • Subramanyam, M. A., Kawachi, I., Berkman, L. F., & Subramanian, S. V. (2010). Socioeconomic inequalities in childhood undernutrition in India: Analyzing trends between 1992 and 2005. PLoS ONE, 5(6), e11392.

    Article  Google Scholar 

  • Subramanyam, M. A., Kawachi, I., Berkman, L. F., & Subramanian, S. V. (2011). Is economic growth associated with reduction in child undernutrition in India? PLoS Medicine, 8(3), 1000424.

    Article  Google Scholar 

  • Tomkins, A. (2000). Malnutrition, morbidity and mortality in children and their mothers. Proceedings of the Nutrition Society, 59(1), 135–146.

    Article  Google Scholar 

  • UNICEF. (2016). Strategy for water, sanitation and hygiene 2016–2030. UNICEF.

    Google Scholar 

  • UNICEF. (2019). Malnutrition. United Nations.

    Google Scholar 

  • UNICEF, WHO, The World Bank group & United Nations Population Division (2011). Levels and trends in child mortality: Report 2011. Oxford University Press 19.

  • United Nations (2015). The Millennium development goals report. Department of Economic and Social Affairs, Population Division. United Nations.

  • United Nations (2018). Sustainable Development Goals Report 2018. Department of Economic and Social Affairs, Population Division. United Nations.

  • United Nations Children’s Fund (UNICEF). (2013). Improving child nutrition, the achievable imperative for global progress (pp. 1–114). UNICEF.

    Google Scholar 

  • United Nations. (2019). World population prospects 2019: Volume I: Comprehensive tables. Department of Economic and Social Affairs, Population Division. United Nations.

  • Vollmer, S., Bommer, C., Krishna, A., Harttgen, K., & Subramanian, S. V. (2017). The association of parental education with childhood undernutrition in low-and middle-income countries: Comparing the role of paternal and maternal education. International Journal of Epidemiology, 46(1), 312–323.

    Google Scholar 

  • Wang, Q., Ni, J., & Tenhunen, J. (2005). Application of a geographically-weighted regression analysis to estimate net primary production of Chinese forest ecosystems. Global Ecology and Biogeography, 14(4), 379–393.

    Article  Google Scholar 

  • WHO. (2006). WHO child growth standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age, methods and development. World Health Organization.

    Google Scholar 

  • WHO. (2011). Child growth standards: WHO Anthro (version 3.2.2, January 2011) and macros. World Health Organization.

    Google Scholar 

  • WHO. (2015). Health in 2015: From MDGs, millennium development goals to SDGs, sustainable development goals. World Health Organization.

    Google Scholar 

  • WHO. (2018). Malnutrition. World Health Organisation.

    Google Scholar 

  • World Health Organization (WHO). (2003). Infant and young child feeding: A tool for assessing national practices, policies and programmes. World Health Organization.

    Google Scholar 

  • Yu, D., Wei, Y. D., & Wu, C. (2007). Modelling spatial dimensions of housing prices in Milwaukee, WI. Environment and Planning B: Planning and Design, 34(6), 1085–1102.

    Article  Google Scholar 

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  1. Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal Nehru University (JNU), New Delhi, India

    Monirujjaman Biswas

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Biswas, M. Identifying Geographical Heterogeneity in Associations between Under-Five Child Nutritional Status and Its Correlates Across Indian Districts. Spat Demogr 10, 143–187 (2022). https://doi.org/10.1007/s40980-022-00104-2

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