Multilevel analysis of geographic variation among correlates of child undernutrition in India

被引:8
|
作者
Jain, Anoop [1 ]
Rodgers, Justin [2 ]
Li, Zhihui [3 ]
Kim, Rockli [4 ,5 ]
Subramanian, S., V [2 ,3 ]
机构
[1] Harvard Med Sch, Global Hlth & Social Med, Boston, MA 02115 USA
[2] Harvard Ctr Populat & Dev Studies, 9 Bow St, Cambridge, MA 02138 USA
[3] Harvard TH Chan Sch Publ Hlth, Dept Social & Behav Sci, Cambridge, MA USA
[4] Korea Univ, Coll Hlth Sci, Div Hlth Policy & Management, Seoul, South Korea
[5] Korea Univ, Interdisciplinary Program Precis Publ Hlth, Dept Publ Hlth Sci, Grad Sch, Seoul, South Korea
来源
MATERNAL AND CHILD NUTRITION | 2021年 / 17卷 / 03期
关键词
child nutrition; international child health nutrition; low‐ income countries; nutritional interventions; social factors; socio‐ economic factors; RELATIVE IMPORTANCE; HEALTH; NUTRITION; POVERTY; INTERVENTIONS; ASSOCIATION; DISTRICTS; HOUSEHOLD; HEIGHT; STATES;
D O I
10.1111/mcn.13197
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual-level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14% to 63%, 10% to 29% for districts and 17% to 62% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific.
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页数:11
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