The levels, distributions of child malnutrition and its potential risk factors are not very well known in Myanmar. The objectives included in this study were: to estimate the current national and subnational prevalence of four types of malnutrition (stunting, wasting, underweight and overweight) among children under 5 in Myanmar; to identify potential risk factors associated with each type of malnutrition and to investigate how the identified risk factors’ distributions explained the regional disparities in malnutrition prevalence.
Data from the Myanmar Demographic and Health Survey 2015–2016 were used to estimate the prevalence of four types of malnutrition at both national and subnational levels (15 regions). Logistic regression models were applied to examine the association between each type of malnutrition and its risk factors, including child’s factors, parental social status and household conditions. The risk factor-adjusted prevalence of the malnutrition was estimated at the subnational level based on the estimated parameters from the regression models.
The national prevalence of stunting, wasting, underweight and overweight in children under 5 was estimated to be 29.1% (95% CI 27.7% to 30.6%), 6.8% (6.0% to 7.6%), 18.3% (17.0% to 19.5%) and 1.5% (1.1% to 1.9%), respectively. Substantial regional variations in the prevalence of each type of malnutrition were observed. Several risk factors of each type of malnutrition were identified, including low birth weight (LBW) and inadequate maternal nutritional status. Except for overweight, regional variations largely persisted even after adjustment for the risk factors investigated.
The prevalence of malnutrition among children under 5 is still high in Myanmar, most commonly stunting. Targeted interventions aimed at prevention of LBW, improving the maternal nutritional status, in addition to other sociodemographic conditions should be encouraged urgently. Further research is necessary to investigate the potential sources of regional variation in prevalence of malnutrition among children under 5 in the country.
Central nervous system (CNS) gliomas are the most common primary intra-axial brain tumours and pose variable treatment response according to their grade, therefore, precise staging is mandatory. Histopathological analysis of surgical tumour samples is still deemed as the state-of-the-art staging technique for gliomas due to the moderate specificity of the available non-invasive imaging modalities. A recently evolved analysis of the tissue water diffusion properties, known as diffusional kurtosis imaging (DKI), is a dimensionless metric, which quantifies water molecules’ degree of non-Gaussian diffusion, hence reflects tissue microenvironment’s complexity by means of non-invasive diffusion-weighted MRI acquisitions. The objective of this systematic review and meta-analysis is to explore the performance of DKI in the presurgical grading of gliomas, both regarding the differentiation between high-grade and low-grade gliomas as well as the discrimination between gliomas and other intra-axial brain tumours.
We will search PubMed, Medline via Ovid, Embase and Scopus in July 2018 for research studies published between January 1990 and June 2018 with no language restrictions, which have reported on the performance of DKI in diagnosing CNS gliomas. Robust inclusion/exclusion criteria will be applied for selection of eligible articles. Two authors will separately perform quality assessment according to the quality assessment of diagnostic accuracy studies-2 tool. Data will be extracted in a predesigned spreadsheet. A meta-analysis will be held using a random-effects model if substantial statistical heterogeneity is expected. The heterogeneity of studies will be evaluated, and sensitivity analyses will be conducted according to individual study quality.
This work will be based on published studies; hence, it does not require institutional review board approval or ethics clearance. The results will be published in peer-reviewed journals.