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

Seiler, Johannes; Harttgen, Kenneth; Kneib, Thomas; Lang, Stefan

doi:10.1016/j.ehb.2020.100950

Cited by 7 publications

(3 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BDR models all parameters of the response distribution based on structured additive predictors and allows to incorporate for example, non-linear effects of metric covariates, spatial effects, or varying effects. Applications of structured additive regression models to topics in Global Public Health are found in several publications [ 39 – 42 ]. This approach permits us to fully analyse the whole distribution [ 41 , 43 ] and our analysis was not restricted to assessing the conditional mean of the height-for-age z-score.…”

Section: Methodsmentioning

confidence: 99%

“…Incorporating the spatial effect on a Markov random field proposal allows to account for the remaining heterogeneity that is not explained by the included covariates. See also Chapter 4 of the methodology manual of BayesX [ 45 ], and Seiler and colleagues [ 42 ] for a more elaborate discussion on the incorporation of the spatio- temporal effect based on a Markov random field prior. This variables are further specified in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background The burden of child under-nutrition still remains a global challenge, with greater severity being faced by low- and middle-income countries, despite the strategies in the Sustainable Development Goals (SDGs). Globally, malnutrition is the one of the most important risk factors associated with illness and death, affecting hundreds of millions of pregnant women and young children. Sub-Saharan Africa is one of the regions in the world struggling with the burden of chronic malnutrition. The 2018 Zambia Demographic and Health Survey (ZDHS) report estimated that 35% of the children under five years of age are stunted. The objective of this study was to analyse the distribution, and associated factors of stunting in Zambia. Methods We analysed the relationships between socio-economic, and remote sensed characteristics and anthropometric outcomes in under five children, using Bayesian distributional regression. Georeferenced data was available for 25,852 children from two waves of the ZDHS, 31% observation were from the 2007 and 69% were from the 2013/14. We assessed the linear, non-linear and spatial effects of covariates on the height-for-age z-score. Results Stunting decreased between 2007 and 2013/14 from a mean z-score of 1.59 (credible interval (CI): -1.63; -1.55) to -1.47 (CI: -1.49; -1.44). We found a strong non-linear relationship for the education of the mother and the wealth of the household on the height-for-age z-score. Moreover, increasing levels of maternal education above the eighth grade were associated with a reduced variation of stunting. Our study finds that remote sensed covariates alone explain little of the variation of the height-for-age z-score, which highlights the importance to collect socio-economic characteristics, and to control for socio-economic characteristics of the individual and the household. Conclusions While stunting still remains unacceptably high in Zambia with remarkable regional inequalities, the decline is lagging behind goal two of the SDGs. This emphasises the need for policies that help to reduce the share of chronic malnourished children within Zambia.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several studies suggest that various factors result in the incidence of stunting in children, such as parenting style (Saleh et al, 2021), exclusive breastfeeding practice (Hadi et al, 2021), psychosocial stimulation (Bogin, 2021), poor environmental hygiene and sanitation (Rah et al, 2020), especially in densely populated areas (Ali, 2021), as well as remote and demographic factors (Seiler et al, 2021). Another essential factor is economic influence (Islam et al, 2020), the mother's education (Anggraini & Romadona, 2020), as well as intermediary factors such as the number of family members, the mother's height and age, as well as the number of children, proximal factors such as exclusive breastfeeding, age, and babies with low birth weight (Chowdhury et al, 2020).…”

Section: Impact Of the Non-cash Food Assistance Program (Bantuan Pang...mentioning

confidence: 99%

Public-Private Partnership in the Implementation of Non-cash Food Assistance Programs in Addressing Poverty, Stunting, and Economic Growth in Takalar Regency, Indonesia

Rusliadi¹,

Widianingsih²,

Buchari³

2023

Preprint

View full text Add to dashboard Cite

Poverty alleviation must be carried out in a planned and sustainable manner by the central government and regional governments, the private sector, and the entire community to achieve a prosperous society by getting special attention from the government. This study aims to analyze the impact of the non-cash food assistance program on poverty alleviation, stunting and economic problems using a public private partnership (PPP) approach that involves the role of the government, the private sector and the community. This study uses a qualitative-explorative research method to examine Indonesia's non-cash food assistance program as a national initiative to fight poverty in the form of food. Data were collected from interviews, field observations, and relevant literature, then Nvivo 12 Pro was used to analyze the results. The location of this research is in Indonesia, namely Takalar Regency. The results of the study show that the implementation of the non-cash basic food assistance program has been effective. The involvement of the government, the private sector, and the community shows this. The success factors for the basic food assistance program are alleviating poverty in Indonesia, reducing stunting rates, and increasing economic growth because people are given a place to be part of small businesses. From the results of this analysis it was concluded that the non-cash basic food assistance program is a special program that can overcome various social problems in society. So that poverty alleviation programs are expected to be sustainable and improved to provide benefits for people's welfare. The implementation of the food aid program also involved several cross-sectoral efforts to channel government assistance.

show abstract

The Indian Enigma revisited

Grafenstein

Klasen²,

Hoddinott

2023

Economics & Human Biology

View full text Add to dashboard Cite

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

Cited by 7 publications

References 55 publications

Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach

Modelling chronic malnutrition in Zambia: A Bayesian distributional regression approach

Public-Private Partnership in the Implementation of Non-cash Food Assistance Programs in Addressing Poverty, Stunting, and Economic Growth in Takalar Regency, Indonesia

The Indian Enigma revisited

Contact Info

Product

Resources

About