Children’s dietary diversity and related factors in Rwanda and Burundi: A multilevel analysis using 2010 Demographic and Health Surveys
Autoři:
Estefania Custodio aff001; Zaida Herrador aff002; Tharcisse Nkunzimana aff001; Dorota Węziak-Białowolska aff003; Ana Perez-Hoyos aff001; Francois Kayitakire aff001
Působiště autorů:
European Commission Joint Research Centre, Ispra, Italy
aff001; Instituto de Salud Carlos III, Centro Nacional de Medicina Tropical, Madrid, Spain
aff002; Sustainability and Health Initiative (SHINE), Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
aff003
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0223237
Souhrn
Background
One of the reported causes of high malnutrition rates in Burundi and Rwanda is children's inadequate dietary habits. The diet of children may be affected by individual characteristics and by the characteristics of the households and the communities in which they live. We used the minimum dietary diversity of children (MDD-C) indicator as a proxy of diet quality aiming at: 1) assess how much of the observed variation in MDD-C was attributed to community clustering, and 2) to identify the MDD-C associated factors.
Methods
Data was obtained from the 2010 Demographic and Health Surveys of Burundi and Rwanda, from which only children 6 to 23 months from rural areas were analysed. The MDD-C was calculated according to the 2007 WHO/UNICEF guidelines. We computed the intra-class coefficient to assess the percentage of variation attributed to the clustering effect of living in the same community. And then we applied two-level logit regressions to investigate the association between MDD-C and potential risk factors following the hierarchical survey structure of DHS.
Results
The MDD-C was 23% in rural Rwanda and 16% in rural Burundi, and a 29% of its variation in Rwanda and 17% in Burundi was attributable to community clustering. Increasing age and living standards were associated with higher MDD-C in both countries, and only in Burundi also increasing level of education of the mother's partner. In Rwanda alone, the increasing ages of the head of the household and of the mother at first birth were also positively associated with it. Despite the identification of an important proportion of the MDD-C variation due to clustering, we couldn't identify any community variable significantly associated with it.
Conclusions
We recommend further research using hierarchical models, and to integrate dietary diversity in holistic interventions which take into account both the household's and the community's characteristics the children live in.
Klíčová slova:
Diet – Food – Food consumption – Children – Rwanda – Socioeconomic aspects of health – Burundi
Zdroje
1. World Health Organization. Guiding principles for feeding non-breastfed children 6–24 months of age. 2005;
2. Dewey KG, Adu-Afarwuah S. Systematic review of the efficacy and effectiveness of complementary feeding interventions in developing countries. Matern Child Nutr. 2008;4: 24–85. doi: 10.1111/j.1740-8709.2007.00124.x 18289157
3. United Nations Children’s Fund (UNICEF). Strategy to Reduce Maternal and Child Undernutrition [Internet]. 2003. http://www.unicef.org/eapro/Strategy_to_reduce_maternal_and_child_undernutrition.pdf
4. Food and Agriculture Organization of the United Nations (FAO). Nutrition Country Paper–Burundi [Internet]. Comprehensive Africa Agriculture Development Programme (CAADP); 2013. http://www.fao.org/fileadmin/user_upload/nutrition/docs/policies_programmes/CAADP/east_central_africa/outputs/country_papers/Burundi_NCP_190213.pdf
5. Food and Agriculture Organization of the United Nations (FAO). Nutrition Country Paper–Rwanda [Internet]. Comprehensive Africa Agriculture Development Programme (CAADP); 2013. http://www.fao.org/fileadmin/user_upload/nutrition/docs/policies_programmes/CAADP/east_central_africa/outputs/country_papers/Rwanda_NCP_210213.pdf
6. National Institute of Statistics of Rwanda (NIRS), Ministry of Health (MOH) [Rwanda], ICF International. Rwanda Demographic and Health Survey 2014–15 [Internet]. Rockville, Maryland, USA: NISR, MOH, and ICF International; 2016. https://dhsprogram.com/pubs/pdf/FR316/FR316.pdf
7. Society for International Development (SID). East Africans Health and Education Status? The State of East Africa Report Series.;
8. Institut de Statistiques et d’Études Économiques du Burundi (ISTEEBU)-Gouvernement du Burundi. Troisième Enquête Démographique et de Santé 2016–2017 [Internet]. 2018. http://microdata.worldbank.org/index.php/catalog/2991
9. Nkunzimana T, Custodio E, Pérez-Hoyos A, Kayitakire F. Assessing MDG Achievements Through Under-5 Child Stunting in the East African Community: Some Insights from Urban Versus Rural Areas in Burundi and Rwanda Using DHS2010. Poverty and Well-Being in East Africa. Springer; 2016. pp. 61–86.
10. World Health Organization (WHO). 2012–2013 Biennium Report.Department of Nutrition for Health and Development: Evidence and Programme Guidance [Internet]. 2014. http://apps.who.int/iris/bitstream/10665/101179/1/WHO_NMH_NHD_EPG_14.1_eng.pdf?ua=1
11. Arimond M, Ruel MT. Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr. 2004;134: 2579–2585. doi: 10.1093/jn/134.10.2579 15465751
12. Food and Agriculture Organization of the United Nations (FAO). Declaration of the World Summit on Food Security [Internet]. Rome, Italy; Nov 16, 2009. http://www.fao.org/fileadmin/templates/wsfs/Summit/Docs/Final_Declaration/WSFS09_Declaration.pdf
13. World Band. The World Bank Data [Internet]. [cited 11 Sep 2019]. https://data.worldbank.org
14. Ministry of Finance and Economic Planning (MINECOFIN) NI of S of R (NISR). Rwanda Fourth Population and Housing Census. Thematic report: Population size, structure and distribution. Rwanda; 2012.
15. Republic du Burundi. Ministere de l’Interieur. Bureau Central du Recensement. Recensement general de la population et de l’habitat du Burundi 2008. Volume 3: Analyse, Tome 6. Etat et Structures de la Population. Burundi; 2008.
16. Indexmundi. Rwanda vs. Burundi—Country Comparison [Internet]. [cited 25 Jul 2018]. https://www.indexmundi.com/factbook/compare/rwanda.burundi
17. National Institure of Statistics of Rwanda (NISR). Environment and Natural Resources [Internet]. 2016. http://www.statistics.gov.rw/publication/eicv-4-thematic-report-environment-and-natural-resources
18. Food and Agriculture Organization of the United Nations (FAO). Rwanda at a glance | FAO in Rwanda | Food and Agriculture Organization of the United Nations. In: FAO in Rwanda [Internet]. [cited 26 Jul 2018]. http://www.fao.org/rwanda/fao-in-rwanda/rwanda-at-a-glance/en/
19. San Pedro, Paula. Investing in agriculture in Burundi [Internet]. Oxfam Research Repor; https://oxfamilibrary.openrepository.com/bitstream/handle/10546/188591/rr-investing-agriculture-burundi-051211-summ-en.pdf?sequence=3
20. Curtis M. Improving African Agriculture Spending: Budget Analysis of Burundi, Ghana, Zambia, Kenya and Sierra Leone. Indep Dev Policy Anal. 2013;
21. United States Agency for International Development (USAID). Guide to DHS Statistics. The Demographic and Health Surveys Program [Internet]. Rockville, Maryland, USA: ICF; 2018. https://dhsprogram.com/pubs/pdf/DHSG1/Guide_to_DHS_Statistics_DHS-7.pdf
22. United States Agency for International Development (USAID). The DHS Program [Internet]. https://dhsprogram.com/
23. Ministère de la Santé Publique et de la Lutte, ICF International., Institut de Statistiques et d’Études Économiques du Burundi (ISTEEBU),. Enquête Démographique et de Santé Burundi 2010. Bujumbura, Burundi: ISTEEBU, MSPLS, et ICF International.; 2010.
24. ICF International.ICF International.ICF InternationalIC NI of S of R (NISR) [Rwanda], Ministry of Health (MOH) [Rwanda],. Rwanda Demographic and Health Survey 2010. Calverton, Maryland, USA: NISR, MOH, and ICF International.;
25. Kolenikov S, Angeles G. Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer? Rev Income Wealth. 2009;55: 128–165.
26. Decancq K, Lugo MA. Weights in multidimensional indices of wellbeing: An overview. Econom Rev. 2013;32: 7–34.
27. Brown ME, Grace K, Shively G, Johnson KB, Carroll M. Using satellite remote sensing and household survey data to assess human health and nutrition response to environmental change. Popul Environ. 2014;36: 48–72. doi: 10.1007/s11111-013-0201-0 25132700
28. Burgert CR, Zachary B, Way A. Response to “Problems of spatial linkage of a geo-referenced demographic and health survey (DHS) dataset to a population census: a case study of Egypt.” Comput Environ Urban Syst. 2012;6: 626–627.
29. Johnson K, Brown ME. Environmental risk factors and child nutritional status and survival in a context of climate variability and change. Appl Geogr. 2014;54: 209–221.
30. Danielson JJ, Gesch DB. Global multi-resolution terrain elevation data 2010 (GMTED2010). US Geological Survey; 2011. Report No.: 2331–1258.
31. Van Velthuizen H. Mapping biophysical factors that influence agricultural production and rural vulnerability. Food and Agriculture Organization of the United Nations (FAO); 2007.
32. Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ. 2002;83: 195–213.
33. Merlo J, Chaix B, Yang M, Lynch J, Råstam L. A brief conceptual tutorial of multilevel analysis in social epidemiology: linking the statistical concept of clustering to the idea of contextual phenomenon. J Epidemiol Community Health. 2005;59: 443–449. doi: 10.1136/jech.2004.023473 15911637
34. United Nations Children’s Fund (UNICEF). UNICEF Data: Monitoring the situation of children and women [Internet]. https://data.unicef.org/topic/nutrition/infant-and-young-child-feeding/
35. Hirvonen K. Rural-urban differences in children’s dietary diversity in Ethiopia. A Poisson decomposition analysis. Ethiopia;
36. Rakotonirainy NH, Razafindratovo V, Remonja CR, Rasoloarijaona R, Piola P, Raharintsoa C, et al. Dietary diversity of 6-to 59-month-old children in rural areas of Moramanga and Morondava districts, Madagascar. PloS One. 2018;13: e0200235. doi: 10.1371/journal.pone.0200235 30005067
37. Kennedy G, Keding GB, Evang, Esther, Rota, Rota Nodari, Giulia, Scheerer, Lars. Nutrition Baseline Survey Summary Report [Internet]. Global Programme Food and Nutrition Security, Enhan ced Resilience; 2017. https://www.snrd-africa.net/wp-content/uploads/2017/07/GIZ_Nutrition-Baseline-Survey-Summary-Report.pdf
38. International Livestock Research Institute (ILRI). Rwanda Livestock Master Plan [Internet]. 2017. http://extwprlegs1.fao.org/docs/pdf/rwa172923.pdf
39. Bizimana C, Usengumukiza F, Kalisa J, Rwirahira J. Trends in Key Agricultural and Rural Development Indicators in Rwanda. Rwanda Strateg Anal Knowl Support Syst SAKSS Minist Agric Anim Resour MINAGRI Kigali. 2012;
40. United States Agency for International Development (USAID), US Government Feed the Future project “Integrating Gender and Nutrition within Extension and Advisory Services” (INGENAES). Burundi: Landscape Analysis [Internet]. 2015. https://www.agrilinks.org/sites/default/files/resource/files/ING%20Landscape%20Study%20%282016%29%20Burundi%20-%20published%202015_09_28.pdf
41. Rawlins R, Pimkina S, Barrett CB, Pedersen S, Wydick B. Got milk? The impact of Heifer International’s livestock donation programs in Rwanda on nutritional outcomes. Food Policy. 2014;44: 202–213.
42. Afolabi KD. Local or Indigenous Chicken Production: A Key to Food Security, Poverty Alleviation, Disease Mitigation and Socio-Cultural Fulfilment in Africa. Sustainable Food Security in the Era of Local and Global Environmental Change. Springer; 2013. pp. 217–229.
43. Oniang’o RK, Mutuku JM, Malaba SJ. Contemporary African food habits and their nutritional and health implications. Asia Pac J Clin Nutr. 2003;12.
44. Issaka AI, Agho KE, Page AN, Burns PL, Stevens GJ, Dibley MJ. Determinants of suboptimal complementary feeding practices among children aged 6–23 months in four anglophone West African countries. Matern Child Nutr. 2015;11: 14–30. doi: 10.1111/mcn.12194 26364789
45. Robert RC, Creed-Kanashiro HM, Penny ME, Marin M, Cottrell B. Dietary Diversity of Children 6–23 months Is Limited by Age Related Complementary Feeding Practices as well as Household Dietary Diversity in Peru, Bangladesh and Sierra Leone. FASEB J. 2017;31: lb454–lb454.
46. Sawadogo S, Yves M-P, Claire M-R, Alain B, Alfred TS, Serge T, et al. Late introduction and poor diversity were the main weaknesses of complementary foods in a cohort study in rural Burkina Faso. Nutrition. 2010;26: 746–752. doi: 10.1016/j.nut.2010.02.010 20579592
47. Ng CS, Dibley MJ, Agho KE. Complementary feeding indicators and determinants of poor feeding practices in Indonesia: a secondary analysis of 2007 Demographic and Health Survey data. Public Health Nutr. 2012;15: 827–839. doi: 10.1017/S1368980011002485 22014663
48. Headey D. An analysis of trends and determinants of child undernutrition in Ethiopia, 2000–2011. Int Food Policy Res Inst IFPRI. 2014;
49. Hirvonen K, Hoddinott J. Agricultural production and children’s diets: evidence from rural Ethiopia. Agric Econ. 2017;48: 469–480.
50. Kumar N, Harris J, Rawat R. If they grow it, will they eat and grow? Evidence from Zambia on agricultural diversity and child undernutrition. J Dev Stud. 2015;51: 1060–1077.
51. Koppmair S, Kassie M, Qaim M. Farm production, market access and dietary diversity in Malawi. Public Health Nutr. 2017;20: 325–335. doi: 10.1017/S1368980016002135 27609557
52. Uzun AK, Orhon FS, Baskan S, Ulukol B. A comparison between adolescent mothers and adult mothers in terms of maternal and infant outcomes at follow-ups. J Matern Fetal Neonatal Med. 2013;26: 454–458. doi: 10.3109/14767058.2012.733748 23020604
53. Abuya B, Onsomu E, Kimani J, Moore D. Influence of maternal education on child immunization and stunting in Kenya. Matern Child Health J. 2011;15: 1389–1399. doi: 10.1007/s10995-010-0670-z 20848172
54. Frempong RB, Annim SK. Dietary diversity and child malnutrition in Ghana. Heliyon. 2017;3: e00298. doi: 10.1016/j.heliyon.2017.e00298 28503669
55. Herrador Z, Perez-Formigo J, Sordo L, Gadisa E, Moreno J, Benito A, et al. Low dietary diversity and intake of animal source foods among school aged children in Libo Kemkem and Fogera Districts, Ethiopia. PloS One. 2015;10: e0133435. doi: 10.1371/journal.pone.0133435 26203904
56. Na M, Aguayo VM, Arimond M, Mustaphi P, Stewart CP. Predictors of complementary feeding practices in Afghanistan: Analysis of the 2015 Demographic and Health Survey. Matern Child Nutr. 2018;14: e12696. doi: 10.1111/mcn.12696 30499256
57. Na M, Aguayo VM, Arimond M, Stewart CP. Risk factors of poor complementary feeding practices in Pakistani children aged 6–23 months: A multilevel analysis of the Demographic and Health Survey 2012–2013. Matern Child Nutr. 2017;13: e12463.
58. Abay K, Hirvonen K. Does market access mitigate the impact of seasonality on child growth? Panel data evidence from northern Ethiopia. J Dev Stud. 2017;53: 1414–1429.
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