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Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

ABSTRACT: Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than average or average and higher) with district as a spatial effect using the 2010 Malawi demographic and health survey data was adopted. A Gaussian model for birth weight in kilograms and a binary logistic model for the binary outcome (size of child at birth) were fitted. Continuous covariates were modelled by the penalized (p) splines and spatial effects were smoothed by the two dimensional p-spline. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was Chitipa and areas with increased risk to less than average size at birth were Chitipa and Mchinji. The study found support for the flexible modelling of some covariates that clearly have nonlinear influences. Nevertheless there is no strong support for inclusion of geographical spatial analysis. The spatial patterns though point to the influence of omitted variables with some spatial structure or possibly epidemiological processes that account for this spatial structure and the maps generated could be used for targeting development efforts at a glance.

SUBMITTER: Ngwira A

PROVIDER: S-EPMC4482619 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

Ngwira Alfred A Stanley Christopher C CC

PloS one 20150626 6

Studies on factors of low birth weight in Malawi have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study aimed at investigating risk factors of low birth weight in Malawi by assuming a flexible approach for continuous covariates and geographical random effect. A Bayesian geo-additive model for birth weight in kilograms and size of the child at birth (less than ave ...[more]

PMID: 26114866

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Project description:BackgroundMalnutrition refers to deficiencies, excesses, or imbalances in a person's intake of energy and/or nutrients. The term malnutrition is a broad term encompassing the three conditions namely undernutrition (micronutrient-related malnutrition), over-nutrition (overweight and obesity), and diet-related non-communicable diseases. Undernutrition is defined as the outcome of insufficient food intake and repeated infectious diseases. Low birth weight (LBW) is cited as a risk factor for mortality and morbidity in young children. However, its association with undernutrition has received little attention. Thus, the current study aimed to examine the relationship between LBW and undernutrition in Malawi.MethodsA cross-sectional study was conducted using data from the Malawi Demographic and Health Survey (MDHS) 2015-16. Children whose Z-scores for each of the following indices height-for-age, weight-for-height, and weight-for-age were below the minus two standard deviations (-2SD) from the median of the World Health Organization's (WHO) reference population were considered to be stunted, wasted and underweight, respectively. LBW was defined as babies whose birth weight was less than 2500 g. The multivariate logistic regression models were performed using surveylogistic while controlling various confounding factors in the six different models.ResultsThe prevalence of stunted, underweight, wasted, and LBW were reported as follows, 39%. 11, 2, and 10% respectively. Compared to children with normal/average birth weight, those with LBW had significantly higher odds of being stunted [adjusted odds ratio (aOR): 1.72; 95% confidence interval (CI): 1.35-2.20), underweight (aOR: 2.30; 95% CI: 1.68-3.14) and wasted (aOR: 1.47; 95% CI: 1.38-4.25) respectively.ConclusionsLBW was a strong predictor of all the three indices of undernutrition. Interventions that aim at improving the growth and development of children during the early years should consider addressing factors that trigger LBW.

Project description:Background and objectiveLow birth weight (LBW) is a major risk factor of child mortality and morbidity during infancy (0-3 years) and early childhood (3-8 years) in low and lower-middle-income countries, including Bangladesh. LBW is a vital public health concern in Bangladesh. The objective of the research was to investigate the socioeconomic inequality in the prevalence of LBW among singleton births and identify the significantly associated determinants of singleton LBW in Bangladesh.Materials and methodsThe data utilized in this research was derived from the latest nationally representative Bangladesh Demographic and Health Survey, 2017-18, and included a total of 2327 respondents. The concentration index (C-index) and concentration curve were used to investigate the socioeconomic inequality in LBW among the singleton newborn babies. Additionally, an adjusted binary logistic regression model was utilized for calculating adjusted odds ratio and p-value (<0.05) to identify the significant determinants of LBW.ResultsThe overall prevalence of LBW among singleton births in Bangladesh was 14.27%. We observed that LBW rates were inequitably distributed across the socioeconomic groups (C-index: -0.096, 95% confidence interval: [-0.175, -0.016], P = 0.029), with a higher concentration of LBW infants among mothers living in the lowest wealth quintile (poorest). Regression analysis revealed that maternal age, region, maternal education level, wealth index, height, age at 1st birth, and the child's aliveness (alive or died) at the time of the survey were significantly associated determinants of LBW in Bangladesh.ConclusionIn this study, socioeconomic disparity in the prevalence of singleton LBW was evident in Bangladesh. Incidence of LBW might be reduced by improving the socioeconomic status of poor families, paying special attention to mothers who have no education and live in low-income households in the eastern divisions (e.g., Sylhet, Chittagong). Governments, agencies, and non-governmental organizations should address the multifaceted issues and implement preventive programs and policies in Bangladesh to reduce LBW.

Dataset Information

Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

Publications

Determinants of Low Birth Weight in Malawi: Bayesian Geo-Additive Modelling.

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