IDEAS home Printed from https://ideas.repec.org/a/eee/ehbiol/v40y2021ics1570677x20302203.html
   My bibliography  Save this article

Modelling children's anthropometric status using Bayesian distributional regression merging socio-economic and remote sensed data from South Asia and sub-Saharan Africa

Author

Listed:
  • Seiler, Johannes
  • Harttgen, Kenneth
  • Kneib, Thomas
  • Lang, Stefan

Abstract

A history of insufficient nutritional intake is reflected by low anthropometric measures and can lead to growth failures, limited mental development, poor health outcomes and a higher risk of dying. Children below five years are among those most vulnerable and, while improvements in the share of children affected by insufficient nutritional intake has been observed, both sub-Saharan Africa and South Asia have a disproportionately high share of growth failures and large disparities at national and sub-national levels. In this study, we use a Bayesian distributional regression approach to develop models for the standard anthropometric measures, stunting and wasting. This approach allows us to model both the mean and the standard deviation of the underlying response distribution. Accordingly, the whole distribution of the anthropometric measures can be evaluated. This is of particular importance, considering the fact that (severe) growth failures of children are defined having a z-score below −2 (−3), emphasising the need to extend the analysis beyond the conditional mean. In addition, we merge individual data taken from the Demographic and Health Surveys with remote sensed data for a large sample of 38 countries located in sub-Saharan Africa and South Asia for the period 1990–2016, in order to combine individual and household specific characteristics with geophysical and environmental characteristics, and to allow for a comparison over time. Our results show besides gender differences across space, and strong non-linear effects of included socio-economic characteristics, in particular for maternal education and the wealth of the household that, surprisingly, in the presence of socio-economic characteristics, remote sensed data does not contribute to variations in growth failures, and including a pure spatial effect excluding remote sensed data leads to even better results. Further, while all regions showed improvements towards the target of the Sustainable Development Goals (SDGs), our analysis identifies hotspots of growth failures at sub-national levels within India, Nigeria, Niger, and Madagascar, emphasising the need to accelerate progress to reach the target set by the SDGs.

Suggested Citation

  • Seiler, Johannes & Harttgen, Kenneth & Kneib, Thomas & Lang, Stefan, 2021. "Modelling children's anthropometric status using Bayesian distributional regression merging socio-economic and remote sensed data from South Asia and sub-Saharan Africa," Economics & Human Biology, Elsevier, vol. 40(C).
    • Handle: RePEc:eee:ehbiol:v:40:y:2021:i:c:s1570677x20302203
    DOI: 10.1016/j.ehb.2020.100950
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1570677X20302203
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ehb.2020.100950?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    2. Alderman, Harold & Lokshin, Michael & Radyakin, Sergiy, 2011. "Tall claims : mortality selection and the height of children," Policy Research Working Paper Series 5846, The World Bank.
    3. Nadja Klein & Thomas Kneib & Stephan Klasen & Stefan Lang, 2015. "Bayesian structured additive distributional regression for multivariate responses," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(4), pages 569-591, August.
    4. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    5. David E. Sahn & David Stifel, 2003. "Exploring Alternative Measures of Welfare in the Absence of Expenditure Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 463-489, December.
    6. Makate, Marshall & Makate, Clifton, 2016. "The causal effect of increased primary schooling on child mortality in Malawi: Universal primary education as a natural experiment," Social Science & Medicine, Elsevier, vol. 168(C), pages 72-83.
    7. Aaron Osgood-Zimmerman & Anoushka I. Millear & Rebecca W. Stubbs & Chloe Shields & Brandon V. Pickering & Lucas Earl & Nicholas Graetz & Damaris K. Kinyoki & Sarah E. Ray & Samir Bhatt & Annie J. Brow, 2018. "Mapping child growth failure in Africa between 2000 and 2015," Nature, Nature, vol. 555(7694), pages 41-47, March.
    8. Diane Dancer & Anu Rammohan & Murray D. Smith, 2008. "Infant mortality and child nutrition in Bangladesh," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1015-1035, September.
    9. Dean Spears, 2012. "How much international variation in child height can sanitation explain?," Working Papers 1438, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
    10. Alderman, Harold & Lokshin, Michael & Radyakin, Sergiy, 2011. "Tall claims: Mortality selection and the height of children in India," Economics & Human Biology, Elsevier, vol. 9(4), pages 393-406.
    11. Adam Storeygard, 2016. "Farther on down the Road: Transport Costs, Trade and Urban Growth in Sub-Saharan Africa," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(3), pages 1263-1295.
    12. Harttgen, Kenneth & Lang, Stefan & Seiler, Johannes, 2019. "Selective mortality and the anthropometric status of children in low- and middle-income countries," Economics & Human Biology, Elsevier, vol. 34(C), pages 257-273.
    13. Smith, Lisa C. & Haddad, Lawrence, 2015. "Reducing Child Undernutrition: Past Drivers and Priorities for the Post-MDG Era," World Development, Elsevier, vol. 68(C), pages 180-204.
    14. Zeileis, Achim & Hornik, Kurt & Murrell, Paul, 2009. "Escaping RGBland: Selecting colors for statistical graphics," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3259-3270, July.
    15. Lucia Breierova & Esther Duflo, 2003. "The Impact of Education on Fertility and Child Mortality: Do Fathers Really Matter Less Than Mothers?," OECD Development Centre Working Papers 217, OECD Publishing.
    16. Hatton, Timothy J. & Sparrow, Robert & Suryadarma, Daniel & van der Eng, Pierre, 2018. "Fertility and the health of children in Indonesia," Economics & Human Biology, Elsevier, vol. 28(C), pages 67-78.
    17. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    18. Umlauf, Nikolaus & Adler, Daniel & Kneib, Thomas & Lang, Stefan & Zeileis, Achim, 2015. "Structured Additive Regression Models: An R Interface to BayesX," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i21).
    19. Payal Hathi & Sabrina Haque & Lovey Pant & Diane Coffey & Dean Spears, 2017. "Place and Child Health: The Interaction of Population Density and Sanitation in Developing Countries," Demography, Springer;Population Association of America (PAA), vol. 54(1), pages 337-360, February.
    20. Brezger, Andreas & Lang, Stefan, 2006. "Generalized structured additive regression based on Bayesian P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 967-991, February.
    21. Grépin, Karen A. & Bharadwaj, Prashant, 2015. "Maternal education and child mortality in Zimbabwe," Journal of Health Economics, Elsevier, vol. 44(C), pages 97-117.
    22. Bauer, Jan M. & Mburu, Samuel, 2017. "Effects of drought on child health in Marsabit District, Northern Kenya," Economics & Human Biology, Elsevier, vol. 24(C), pages 74-79.
    23. Krivobokova, Tatyana & Kneib, Thomas & Claeskens, Gerda, 2010. "Simultaneous Confidence Bands for Penalized Spline Estimators," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 852-863.
    24. Aizawa, Toshiaki, 2019. "Ex-ante Inequality of Opportunity in Child Malnutrition: New Evidence from Ten Developing Countries in Asia," Economics & Human Biology, Elsevier, vol. 35(C), pages 144-161.
    25. Helene Roth & Stefan Lang & Helga Wagner, 2015. "Random intercept selection in structured additive regression models," Working Papers 2015-02, Faculty of Economics and Statistics, Universität Innsbruck.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. von Grafenstein, Liza & Klasen, Stephan & Hoddinott, John, 2023. "The Indian Enigma revisited," Economics & Human Biology, Elsevier, vol. 49(C).
    2. Isabel Günther & Kenneth Harttgen & Johannes Seiler & Jürg Utzinger, 2022. "An index of access to essential infrastructure to identify where physical distancing is impossible," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kenneth Harttgen & Stefan Lang & Judith Santer & Johannes Seiler, 2017. "Modeling under-5 mortality through multilevel structured additive regression with varying coefficients for Asia and Sub-Saharan Africa," Working Papers 2017-15, Faculty of Economics and Statistics, Universität Innsbruck.
    2. Harttgen, Kenneth & Lang, Stefan & Seiler, Johannes, 2019. "Selective mortality and the anthropometric status of children in low- and middle-income countries," Economics & Human Biology, Elsevier, vol. 34(C), pages 257-273.
    3. Caitlin S. Brown & Martin Ravallion & Dominique van de Walle, 2017. "Are Poor Individuals Mainly Found in Poor Households? Evidence using Nutrition Data for Africa," NBER Working Papers 24047, National Bureau of Economic Research, Inc.
    4. Jamie Roberman & Theophilus I. Emeto & Oyelola A. Adegboye, 2021. "Adverse Birth Outcomes Due to Exposure to Household Air Pollution from Unclean Cooking Fuel among Women of Reproductive Age in Nigeria," IJERPH, MDPI, vol. 18(2), pages 1-15, January.
    5. Diane Coffey & Ashwini Deshpande & Jeffrey Hammer & Dean Spears, 2019. "Local Social Inequality, Economic Inequality, and Disparities in Child Height in India," Demography, Springer;Population Association of America (PAA), vol. 56(4), pages 1427-1452, August.
    6. Derek Headey & David Stifel & Liangzhi You & Zhe Guo, 2018. "Remoteness, urbanization, and child nutrition in sub‐Saharan Africa," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 765-775, November.
    7. Samia Badji, 2016. "Mother's Education and Increased Child Survival in Madagascar: What Can We Say?," Working Papers 1635, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    8. Richard Akresh & Sonia Bhalotra & Marinella Leone & Una Osili, 2023. "First- and Second-Generation Impacts of the Biafran War," Journal of Human Resources, University of Wisconsin Press, vol. 58(2), pages 488-531.
    9. Pallavi Panda, 2020. "Selective Mortality and Malnutrition in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(4), pages 861-890, December.
    10. Richard Akresh & Sonia Bhalotra & Marinella Leone & Una Osili, 2017. "Hunger Games: First and Second Generation Impacts of the Biafran War," HiCN Working Papers 254, Households in Conflict Network.
    11. Marshall Makate, 2016. "Education Policy and Under-Five Survival in Uganda: Evidence from the Demographic and Health Surveys," Social Sciences, MDPI, vol. 5(4), pages 1-17, October.
    12. Headey, Derek D. & Hoddinott, John F., 2014. "Understanding the rapid reduction of undernutrition in Nepal, 2001-2011:," IFPRI discussion papers 1384, International Food Policy Research Institute (IFPRI).
    13. Chibuzor Christopher Nnanatu & Glory Atilola & Paul Komba & Lubanzadio Mavatikua & Zhuzhi Moore & Dennis Matanda & Otibho Obianwu & Ngianga-Bakwin Kandala, 2021. "Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-31, February.
    14. Nie, Peng & Rammohan, Anu & Gwozdz, Wencke & Sousa-Poza, Alfonso, 2016. "Developments in Undernutrition in Indian Children Under Five: A Decompositional Analysis," IZA Discussion Papers 9893, Institute of Labor Economics (IZA).
    15. Ngianga-Bakwin Kandala & Chibuzor Christopher Nnanatu & Glory Atilola & Paul Komba & Lubanzadio Mavatikua & Zhuzhi Moore & Gerry Mackie & Bettina Shell-Duncan, 2019. "A Spatial Analysis of the Prevalence of Female Genital Mutilation/Cutting among 0–14-Year-Old Girls in Kenya," IJERPH, MDPI, vol. 16(21), pages 1-28, October.
    16. Shahjahan, Md & La Mattina, Giulia & Ayyagari, Padmaja, 2022. "The Impact of Maternal Education on Child Immunization: Evidence from Bangladesh," IZA Discussion Papers 15553, Institute of Labor Economics (IZA).
    17. Bahadır Dursun & Resul Cesur & Inas R. Kelly, 2022. "Mandatory Schooling of Girls Improved Their Children's Health: Evidence from Turkey's 1997 Education Reform," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(3), pages 824-858, June.
    18. Makate, Marshall & Makate, Clifton, 2016. "Is poor sanitation killing more children in rural Zimbabwe? Results of propensity score matching method," MPRA Paper 72831, University Library of Munich, Germany, revised 02 Aug 2016.
    19. Ickowitz, Amy & Powell, Bronwen & Salim, Mohammad & Sunderland, Terry, 2013. "Dietary quality and tree cover in Africa," MPRA Paper 52906, University Library of Munich, Germany.
    20. Nguyen-Phung, Hang Thu, 2023. "The impact of maternal education on child mortality: Evidence from an increase tuition fee policy in Vietnam," International Journal of Educational Development, Elsevier, vol. 96(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ehbiol:v:40:y:2021:i:c:s1570677x20302203. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622964 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.