This paper explores the relationship between household wealth and nutritional status of pre-school children in Bangladesh using the nationally representative 2007 Bangladesh Demographic and Health Survey data. Chronic malnutrition was measured by z-score of height-for-age and the effect of household wealth on adverse childhood growth rate was assessed by multivariate logistic regression analyses. Overall, 43% of the children were stunted. The multivariate binary logistic regression analysis yielded significantly increased risk of stunting among the poorest (OR=2.26, 95% CI=1.77-2.89) as compared to the richest. The multivariate multinomial logistic regression produced elevated risk of moderate stunting (OR=1.98, 95% CI=1.50-2.61) and severe stunting (OR=2.88, 95% CI=2.00-4.14) of children in the poorest category compared to their richest counterparts. Children's age, duration of breastfeeding, mother's education, body mass index, mother's working status and place of region were also identified as important determinants of children's nutritional status. The findings suggest that apart from poverty reduction, maternal education, and strengthening of child and maternal health care services are important to improve health and nutritional status of the children.
Download full-text PDF |
Source |
---|
Probiotics Antimicrob Proteins
January 2025
College of Food Science and Technology, Henan Agricultural University, Zhengzhou, 450002, People's Republic of China.
With the in-depth and comprehensive research on probiotic Bacillus, it has become a hot topic in food science. However, the current status of research using bibliometric analysis to assess the application of probiotic Bacillus in food science has not been comprehensively reviewed. The Web of Science (WOS) database was used in this review's bibliometric analysis to determine the hotspots for research as well as the extent of completed experiments.
View Article and Find Full Text PDFJ Acad Nutr Diet
January 2025
Department of Nutritional Sciences, University of Michigan School of Public Health. Electronic address:
Background: Parents are important conduits of weight- and health-related messaging. Weight-related communication and approaches to child feeding used by parents may reflect their past experiences with weight stigma and are understudied pathways through which intergenerational weight stigma may be transmitted.
Objective: To examine how experienced and internalized weight stigma among parents of children with higher weights are associated with weight-related communication and the feeding practices they use.
J Nutr
January 2025
Department of Human Physiology of the Chair of Preclinical Sciences, Medical University in Lublin, Lublin, Poland.
Background: Systemic inflammation plays a crucial role in the development and progression of chronic heart failure (CHF) across all phenotypes. The continuous release of pro-inflammatory cytokines causes muscle atrophy and adipocyte breakdown, ultimately resulting in cachexia. Long non-coding RNAs (lncRNAs) are emerging as potential biomarkers associated with cachexia, as they indirectly regulate muscle and fat tissue metabolism.
View Article and Find Full Text PDFMol Cell Endocrinol
January 2025
Gastric Cancer Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, China. Electronic address:
Objective: The gut-brain axis (GBA) is involved in the modulation of multiple physiological activities, and the vagus nerve plays an important role in this process. However, the association between vagus nerve function and nutritional regulation remains unclear. Here, we explored changes in the nutritional status of mice after vagotomy and investigated the underlying mechanisms responsible for these changes.
View Article and Find Full Text PDFNutrition
December 2024
Central University of Jharkhand, Ranchi, Jharkland, India. Electronic address:
Objectives: Childhood stunting remains a significant public health issue in India, affecting approximately 35% of children under 5. Despite extensive research, existing prediction models often fail to incorporate diverse data sources and address the complex interplay of socioeconomic, demographic, and environmental factors. This study bridges this gap by employing machine learning methods to predict stunting at the household level, using data from the National Family Health Survey combined with satellite-driven datasets.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!