Determinants of infant mortality in last two decades: a bibliometric analysis

Taşkaya, Serap; Demirkiran, Mustafa

doi:10.18203/2394-6040.ijcmph20160731

Cited by 6 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By implication, the sex of a child, the mother's age, pre-term birth and giving birth at home do not matter much in child survival if other conditionshaving access to financial resources, having a higher education, and not living in the Northwest or Southeast -are right. This contradicts some previous studies [9][10][11][12][13][14][15][16] that concluded that these variables matter in child survival. On the strength of our analysis, we argue that a pre-term birth stands a good survival chance if the socio-cultural context is right, if resources are available to provide quality healthcare and nourishment for the child and the mother has higher education.…”

Section: Discussioncontrasting

confidence: 87%

“…Proximate predictors of child deaths include sociodemographic factors [5][6][7][8], biomedical factors such as birth interval, weight and gestation period, sex of child and diseases [9][10][11][12][13][14][15][16] and health-seeking behavior and barriers to care [17,18]. Research shows that education, income, and access to healthcare resources (including safe drinking water and sanitation) enhance child survival globally [5-8, 10, 15, 19, 20], and countries having higher inequality in access to education, income and healthcare resources also have higher mortality rates [5,8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data

et al. 2022

View full text Add to dashboard Cite

Background Nigeria’s child health profile is quite concerning with an infant mortality rate of 67 deaths per 1000 live births and a significant slowing down in progress towards improving child health outcomes. Nigeria’s 2018 Demographic and Health Survey (DHS) suggests several bio-demographic risk factors for child death, including mother’s poor education, poverty, sex of child, age of mother, and location (rural vs urban) but studies are yet to explore the predictive power of these variables on infant survival in Nigeria. Methods The study extracted data for all births in the last 12 months preceding the 2018 Nigeria DHS and used the Cox proportional hazard model to predict infant survival in Nigeria. Failure in this analysis is death with two possible outcomes – dead/alive – while the survival time variable is age at death. We censored infants who were alive at the time of the study on the day of the interview. Covariates in the analysis were: age of mother, education of mother, wealth quintile, sex of child, location, region, place of delivery, and age of pregnancy. Results The study found that a higher education of a mother compared to no education (β = .429; p-value < 0.05); belonging to a household in the richer wealth quintile (β = .618; p-value < 0.05) or the highest quintile (β = .553; p-value < 0.05), compared to the lowest wealth quintile; and living in North West (β = 1.418; p-value < 0.05) or South East zone (β = 1.711; p-value < 0.05), significantly predict infant survival. Conclusion Addressing Nigeria’s infant survival problem requires interventions that give attention to the key drivers – education, socio-economic status, and socio-cultural contextual issues. We therefore recommend full implementation of the universal basic education policy, and child health education programs targeted at mothers as long- and short-term solutions to the problem of poor child health outcomes in Nigeria. We also argue in favor of better use of evidence in policy and program development in Nigeria.

show abstract

Section: Discussioncontrasting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The infant mortality rate (IMR), characterised as the number of deaths in children under one year of age for every 1,000 live births, has been viewed as a profoundly delicate measure of public health [1]. Infant mortality is found to be one of the most significant parts of under-five child mortality as a vulnerable age group for medicinal administrations, which is particularly necessary for the foundation of wellbeing, social prosperity and improvement of life standard [2][3][4][5][6][7]. The mortality rate of infants under one year is one of the most deciding indicators of a nation's advancement [8].…”

Section: Introductionmentioning

confidence: 99%

Exploring the influencing factors for infant mortality: a mixed-method study of 24 developing countries based on demographic and health survey data

ISLAM¹,

TABASSUM²,

MONI³

2022

fmpcr

View full text Add to dashboard Cite

Background. Infant mortality is a salient indicator for appraising the quality of the healthcare infrastructures of a country. To achieve the sustainable development goal, the infant mortality rate should be reduced to the indicated level. On account of this, it is requisite to point out the associated factors of infant mortality and provide action plans for monitoring them.Objectives. This study aimed to discover the prevalence of infant mortality and assess how different factors influence infant mortality in 24 developing countries by utilising the latest Demographic and Health Survey (DHS) data. Material and methods. This study used a mixed-method design to assemble cross-sectional studies to integrate data from 24 other countries due to the widening perspective of infant mortality. Descriptive analysis, binary logistic regression model, random-effect meta-analysis and forest plot have been used for the analyses. Results. The binary logistic regression model for Bangladesh revealed that a higher education level of fathers (OR: 0.344, 95% CI: 0.147; 0.807), being 2 nd born or above order infant (OR: 0.362, 95% CI: 0.248; 0.527), undergoing antenatal care (ANC) (OR: 0.271, 95% CI: 0.192; 0.382 for 1-4 visits) and undergoing postnatal care (PNC) (OR: 0.303, 95% CI: 0.216; 0.425) were statistically significant determinants of lowering infant death. While carrying multiple foetuses (OR: 6.634, 95% CI: 3.247; 13.555) was shown to be a risk factor of infant mortality. The most significant factors influencing infant mortality for developing countries were the number of foetuses (OR: 0.193, 95% CI: 0.176; 0.213), undergoing ANC (OR: 0.356, 95% CI: 0.311; 0.407), undergoing PNC (OR: 0.302, 95% CI: 0.243; 0.375) and the size of the children (OR: 0.653, 95% CI: 0.588; 0.726). Conclusions. In this study, the number of the foetuses, undergoing ANC and PNC, mother's education, fathers' education and size of the children were the most significant factors affecting infant mortality in developing countries. Thusly, anticipation and control projects need to be taken considering the outcome of this study to reduce the infant mortality.

show abstract

“…The infant mortality rate (IMR), characterized as the number of deaths in youngsters under one year of age for every 1000 live births, has been viewed as a profoundly delicate measure of public health 1 . Infant mortality is found to be one of the most significant parts of under-five child mortality as a vulnerable age group for medicinal administrations, which is particularly necessary for the foundation of wellbeing, social prosperity, and endorsement of standard life [2][3][4][5][6][7] . The mortality rate of infants underneath one year is one of the most deciding indicators of a nation's advancement 8 .…”

Section: Introductionmentioning

confidence: 99%

Exploring the Influencing Factors for Infant Mortality: A Mixed-Method Study of 24 Developing Countries Based on Demographic and Health Survey data

Islam

Tabassum

Moni

2021

Preprint

View full text Add to dashboard Cite

Objective: This study aimed to discover the prevalence of infant mortality and to assess how different factors influence infant mortality in 24 developing countries by utilizing the latest DHS data. Methods: This study used a mixed-method design to assemble cross-sectional studies to integrate data from 24 other countries due to a widening perspective of infant mortality. Most recent available DHS data of 24 different developing countries from the year 2013 to 2019 was used to conduct the study. Descriptive analysis, binary logistic regression model, random-effect meta-analysis, and forest plot have been used for the final analyses. Results: Binary logistic regression model revealed for Bangladesh that, higher education level of fathers (OR: 0.344, 95% CI: 0.147; 0.807), being 2nd born or above order infant (OR: 0.362, 95% CI: 0.248, 0.527), taking ANC (OR: 0.271, 95% CI: 0.192; 0.382 for 1-4 visits), taking PNC (OR: 0.303, 95% CI: 0.216; 0.425) were statistically significant determinants of lowering infant death. While carrying multiple fetus (OR: 6.634, 95% CI: 3.247; 13.555) was exposed as a risk factor of infant mortality. Most significant factors influencing infant mortality for all 24 developing countries were number of fetus (OR: 0.193, 95% CI: 0.176; 0.213), taking ANC (OR: 0.356, 95% CI: 0.311; 0.407) and taking PNC (OR: 0.302, 95% CI: 0.243; 0.375). Conclusion In this study, the number of the fetus, taking ANC and PNC, was the most significant factor affecting the risk of infant mortality in developing countries. So, anticipation and control projects ought to be taken in the field in regard to these hazard factors.

show abstract

Determinants of infant mortality in last two decades: a bibliometric analysis

Cited by 6 publications

References 11 publications

Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data

Background predictors of time to death in infancy: evidence from a survival analysis of the 2018 Nigeria DHS data

Exploring the influencing factors for infant mortality: a mixed-method study of 24 developing countries based on demographic and health survey data

Exploring the Influencing Factors for Infant Mortality: A Mixed-Method Study of 24 Developing Countries Based on Demographic and Health Survey data

Contact Info

Product

Resources

About