How much does birth weight matter for child health in developing countries? Estimates from siblings and twins

McGovern, Mark E.

doi:10.1002/hec.3823

Cited by 34 publications

(29 citation statements)

References 111 publications

(174 reference statements)

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“…This paper followed analytical and empirical literature on childhood mortality to select crucial variables for the child survival analysis. [17][18][19][20][21]24 This study followed "UNICEF definition of under-five mortality", as follows, "probability of dying between birth and exactly five years of age expressed per 1000 livebirths" 4 The extensive information from birth histories of women aged 15-49 was used to compute the hazard ratio of dying between birth and exactly five years of age. Finally, the hazard ratio was used as an outcome variable.…”

Section: Description Of Variablesmentioning

confidence: 99%

Crucial predicting factors of under-five mortality in Sierra Leone

Naz

Patel

Uzoma

2020

Clinical Epidemiology and Global Health

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includes in countries which exhibit the highest prevalence of under-five mortality in the world. A range of factors are known to have challenged the under-five survival in the country; some comprise outbreak of epidemics, socioeconomic inequalities, regional disparities, and unsuccessful implementation of healthcare initiatives. The present study aims to identify crucial predictors of under-five survival. Methods: This paper used the Sierra Leone Demographic and Health Survey (SLDH, 2013). A Cox Proportional Hazards Model was applied to the sample of 24,742 children to analyze the adjusted and unadjusted hazards ratio of crucial risk factors of under-five mortality. Results: The results show that birth interval and birth size are leading risk factors of under-five mortality in Sierra Leone. A birth spacing exceeding three years is associated with the lowest risk compared to 2-3 years and lesser than two years. The average or larger birth size has the lowest hazards followed by smaller than average, and the magnitude of the effect remains the same in adjusted and unadjusted models. The wealth status is a crucial predictor only in the unadjusted model. Mother's age, sex of the child, and a number of children in the household are significant covariates. Conclusion: Given the research findings, this study recommends for reorientation of reproductive healthcare strategies to target the younger mother and birth-spacing, and integration of nutrition-related interventions with the maternal healthcare initiatives to influence the child birth-size.

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Section: Description Of Variablesmentioning

confidence: 99%

Crucial predicting factors of under-five mortality in Sierra Leone

Naz

Patel

Uzoma

2020

Clinical Epidemiology and Global Health

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“…Low birth weight is the strongest predictor of stunting in Malda district. Association between low birth weight and stunting has been shown by several studies (45,48,49,51). As per medical concern, intra-uterine growth retardation (IUGR) is the main cause of low birth weight in developing countries (89).…”

Section: Discussionmentioning

confidence: 99%

“…It has been found that individual child characteristics, e.g., child's age, sex, birth interval, birth order and birth weight are the associated factors of stunting (32,34,36,37,43,44). Many studies found that children born with low birth weight are more prone to become stunted in their childhood (45)(46)(47)(48)(49)(50)(51). A multi-country analysis based in 137 developing countries found that preterm birth or short gestational age is the leading cause of stunting among children of 24-35 months old (52).…”

Section: Review Of the Literaturementioning

confidence: 99%

Nutritional status and its concomitant factors among pre-school children in Malda, India: A micro-level study using a multilevel approach

Sk¹,

Banerjee²,

Mj³

2020

Preprint

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BackgroundMalnutrition was the main cause of death among children below five years in every Indian state in 2017. Despite several flagship programmes and schemes implemented by the Indian Government, the latest edition of the Global Nutrition Report 2018 addressed that India tops in the number of stunted children, that is a matter of concern. Thus, a micro-level study was designed to know the level of nutritional status and to study this by various disaggregate levels, as well as to examine the risk factors of stunting among pre-school children aged 36-59 months in Malda. MethodA primary quantitative survey was conducted using structured questionnaires following a multi-stage, stratified simple random sampling procedure. A sum of 731 samples collected. Anthropometric measures of children were collected following the WHO child growth standard. Children were classified as stunted, wasted and underweight if their HAZ, WHZ and WAZ scores, respectively were less than −2SD. Univariate descriptive statistics have been carried out to describe the sample characteristics and random intercept multilevel logistic regression model has been employed to estimate the effects of possible risk factors on childhood stunting. ResultsThe prevalence of stunting in the study area is 40 per cent among children aged 36-59 months which is very high prevalence as per the WHO’s cut-off values (≥40 per cent) for public health significance. Results of the multilevel analysis revealed that preceding birth interval, low birth weight, duration of breastfeeding, mother’s age at birth, mother’s education and occupation are the associated risk factors of stunting. Among them, low birth weight (OR 2.22, 95%CI: 1.44-3.41) and bidi worker as mothers’ occupation (OR 1.92, 95%CI: 1.18-3.12) are the most influencing factors of stunting. Further, about 14 per cent and 86 per cent variation in stunting lies at community and child/household level respectively.ConclusionSpecial attention needs to be placed for the modifiable risk factors of childhood stunting. Policy interventions should direct community health workers to encourage women as well as their male partner to increase birth interval using various family planning practices, provide extra care for low birth weight baby that can help to reduce childhood stunting.

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“…Linear models have the advantage of well-established use of essential techniques: differencing between twins (to account for sample selection and unobserved heterogeneity) combined with instrumenting noisy differences (to account for measurement error). Not surprisingly, the linear probability model is a common choice in analyses of twin data, including studies of mortality outcomes (e.g., Almond et al, 2005;McGovern, 2019). Behrman et al (1994) lay out a model for determining schooling and wages for twins.…”

Section: Methodsmentioning

confidence: 99%

Health Endowments, Schooling Allocation in the Family, and Longevity: Evidence from US Twins

2018

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We thank participants of these meetings for helpful suggestions and stimulating discussions. For their comments and suggestions, the authors wish to thank Kathy Anderson, Andrew Goodman-Bacon, Rong Hai, Anna Sanz-de-Galdeano, and four anonymous NSF referees. The authors are especially grateful to Jere Behrman for sharing the data from the Socioeconomic Survey of Twins and commenting on our drafts, and to Federico Gutierrez for his considerable help in conceiving and designing the analysis of schooling allocation in the family.

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How much does birth weight matter for child health in developing countries? Estimates from siblings and twins

Cited by 34 publications

References 111 publications

Crucial predicting factors of under-five mortality in Sierra Leone

Crucial predicting factors of under-five mortality in Sierra Leone

Nutritional status and its concomitant factors among pre-school children in Malda, India: A micro-level study using a multilevel approach

Health Endowments, Schooling Allocation in the Family, and Longevity: Evidence from US Twins

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