Application of Structural Equation Modeling to Infant Mortality Rate in Egypt

Abdelkhalek, Fatma; Bolla, Marianna

doi:10.1007/978-3-030-44695-6_7

Cited by 3 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For more details about these indicators, see Abdelkhalek and Bolla (2020). Through the CVAR(p) model, we show the contemporaneous and lagged time effects between the components.…”

Section: Imr (Infant Mortality Rate) Longitudinal Datamentioning

confidence: 99%

“…Similarly to the unrestricted situation, the non-zero upper-diagonal entries of A (see Table 16) represent the path coefficients of the contemporaneous causal effects of X t , while the entries of the matrix B (see Table 17) represent the one time lag causal effects of the X t−1 components on the X t components. Abdelkhalek and Bolla (2020).…”

Section: Abbreviationsmentioning

confidence: 99%

See 1 more Smart Citation

Causal Vector Autoregression Enhanced with Covariance and Order Selection

Bolla

Wang

et al. 2023

Econometrics

View full text Add to dashboard Cite

A causal vector autoregressive (CVAR) model is introduced for weakly stationary multivariate processes, combining a recursive directed graphical model for the contemporaneous components and a vector autoregressive model longitudinally. Block Cholesky decomposition with varying block sizes is used to solve the model equations and estimate the path coefficients along a directed acyclic graph (DAG). If the DAG is decomposable, i.e., the zeros form a reducible zero pattern (RZP) in its adjacency matrix, then covariance selection is applied that assigns zeros to the corresponding path coefficients. Real-life applications are also considered, where for the optimal order p≥1 of the fitted CVAR(p) model, order selection is performed with various information criteria.

show abstract

“…For more details about these indicators, see Abdelkhalek and Bolla (2020). Through the CVAR(p) model, we show the contemporaneous and lagged time effects between the components.…”

Section: Imr (Infant Mortality Rate) Longitudinal Datamentioning

confidence: 99%

Section: Abbreviationsmentioning

confidence: 99%

Causal Vector Autoregression Enhanced with Covariance and Order Selection

Bolla

Wang

et al. 2023

Econometrics

View full text Add to dashboard Cite

show abstract

“…Unlike multivariable regression models, path analysis delineates pathways to outcome, in this case a chain of factors that leads to child survival (Jeon 2015). Other studies have demonstrated independent variables of child survival through path analysis in resource-limited countries (Ricci et al 2019;Abdelkhalek and Bolla 2020;Kananura et al 2017;Nguyen and Nguyen 2020;Naghavi-Behzad et al 2014). These studies, however, have used ecological data (Ricci et al 2019;Abdelkhalek and Bolla 2020;Nguyen and Nguyen 2020) or are hospital-based (Naghavi-Behzad et al 2014), limiting inferences that can be drawn at individual level or to a wider population, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Other studies have demonstrated independent variables of child survival through path analysis in resource-limited countries (Ricci et al 2019;Abdelkhalek and Bolla 2020;Kananura et al 2017;Nguyen and Nguyen 2020;Naghavi-Behzad et al 2014). These studies, however, have used ecological data (Ricci et al 2019;Abdelkhalek and Bolla 2020;Nguyen and Nguyen 2020) or are hospital-based (Naghavi-Behzad et al 2014), limiting inferences that can be drawn at individual level or to a wider population, respectively. Previous study in sub-Saharan Africa showed, however, that poverty and maternal illiteracy are indirectly associated with child mortality, whereas child's nutritional status has direct association with child mortality (Ricci et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Disentangling the link between social determinants of health and child survival in Nigeria during the Sustainable Development Goals era: a hierarchical path analysis of time-to-event outcome

Adeyinka,

Muhajarine

2023

J. Biosoc. Sci.

View full text Add to dashboard Cite

While social determinants of health have been perennially linked to child survival in resource-limited countries, the precise and tested pathways to effect are not clearly understood. The objective of this study was therefore to identify the critical pathways as posited a priori in a model through which social factors (at maternal, household, and community levels) determine neonatal, infant, and under-five mortalities in Nigeria. Using a novel analytic approach (hierarchical path modelling for predicting accelerated failure time) to estimate (in)direct and total effects of social determinants of child survival, we analysed 30,960 live births (weighted data for representativeness), obtained from the 2016/2017 Nigeria Multiple Indicator Cluster Survey. There were three outcome variables: time until occurrence of neonatal, infant, and under-five mortalities. The independent variables were layered factors related to child, maternal, household and community. Geographical region, rurality of residence, infrastructural development, maternal education, contraceptive use, marital status, and maternal age at birth were found to operate more indirectly on neonatal, infant, and under-five survival. Child survival is due to direct effects of child’s sex (female), gestational type (singleton), birth spacing (children whose mothers delivered at least two years apart), and maternal age at delivery (20–34 years). According to the path coefficients, the indirect effects of geographical regions are the most influential determinants of child survival, accounting for 30% (neonatal), 37.1% (infant) and 39.9% (under-five) of the total effects. This study offers comprehensive set of factors, and linked pathways, at the maternal, household, and community levels that are associated with child survival in Nigeria. To accelerate progress towards Sustainable Development Goal targets for child survival and reduce geographical inequities, stakeholders should implement more impactful policies that promote maternal education, contraceptive use and improve living conditions of women (especially in rural areas of northern Nigeria). Future research should focus on identifying the most effective interventions for addressing these social determinants of child survival in Nigeria.

show abstract

Measures of Lifespan Length and Variation Using a Mixture Model: The Case of Egypt

Siam,

Sayed,

El-Zeini

2024

Statistics, Politics and Policy

View full text Add to dashboard Cite

Monitoring the changes in mortality patterns and levels requires studying mortality models and measures of lifespan length and variation. Measures of lifespan length and variation can be obtained from life tables or from mortality modes. In this paper, measures of lifespan length and variation are presented for mixture model introduced by Zanotto, L., V. Canudas-Romo, and S. Mazzuco. 2021. “A Mixture-Function Mortality Model: Illustration of the Evolution of Premature Mortality.” European Journal of Population 37 (1): 1–27. This was applied to the case of Egypt for males and females in the period 1950–2021. The mixture model was able to fit Egypt’s mortality pattern well for both males and females. The calculated measures of lifespan length and variation show that there is an increasing longevity and a declining variation of age at death distribution across time for both males and females.

show abstract

Application of Structural Equation Modeling to Infant Mortality Rate in Egypt

Cited by 3 publications

References 7 publications

Causal Vector Autoregression Enhanced with Covariance and Order Selection

Causal Vector Autoregression Enhanced with Covariance and Order Selection

Disentangling the link between social determinants of health and child survival in Nigeria during the Sustainable Development Goals era: a hierarchical path analysis of time-to-event outcome

Measures of Lifespan Length and Variation Using a Mixture Model: The Case of Egypt

Contact Info

Product

Resources

About