BackgroundAnemia is a global public health problem but the burden of anemia is disproportionately borne among children in developing countries. Anemia in early stages of life has serious consequences on the growth and development of the children. We examine the prevalence of anemia, possible association between anemia and different socio-economic, demographic, health and other factors among children with ages from 6 to 59 months from the nationally representative 2011 Bangladesh Demographic and Health Survey (BDHS).MethodsData on hemoglobin (Hb) concentration among the children aged 6–59 months from the most recent BDHS (2011) were used. This nationally representative survey allowed a multistage stratified cluster sampling design and provided data on a wide range of indicators such as fertility, mortality, women and child health, nutrition and other background characteristics. Anemia status was determined using hemoglobin level (<11.0 g/dl), and weighted prevalence of childhood anemia along with 95 % confidence intervals were provided. We also examined the distribution of weighted anemia prevalence across different groups and performed logistic regression to assess the association of anemia with different factors.ResultsA total of 2171 children aged 6–59 months were identified for this analysis, with weighted prevalence of anemia being 51.9 % overall- 47.4 % in urban and 53.1 % in rural regions. Results of a multivariable logistic regression analysis showed that, children below 24 months of age (odds ratio, [OR] 3.01; 95 % confidence interval [CI] 2.38-3.81), and those from an anemic mother (OR 1.80; 95 % CI 1.49-2.18) were at higher risk of anemia. Childhood anemia was significantly associated with chronic malnutrition of child, source of drinking water, household wealth and geographical location (defined by division).ConclusionsA high prevalence of anemia among 6–59 months aged children was observed in Bangladesh. Given the negative impact of anemia on the development of children in future, there is an urgent need for effective and efficient remedial public health interventions.
BackgroundLow birth weight (LBW) remains a leading global cause of childhood morbidity and mortality. This study leverages a large national survey to determine current prevalence and socioeconomic, demographic and heath related factors associated with LBW in Bangladesh.MethodsData from the Multiple Indicator Cluster Survey (MICS) 2012–13 of Bangladesh were analyzed. A total of 2319 women for whom contemporaneous birth weight data was available and who had a live birth in the two years preceding the survey were sampled for this study. However, this analysis only was able to take advantage of 29% of the total sample with 71% missing birth weight for newborns. The indicator, LBW (< 2500 g) of infants, was examined as the outcome variable in association with different socioeconomic, demographic and health-related covariates. Mixed-effects logistic regression was performed to identify possible factors related to LBW.ResultsIn the selected sub-sample, about 20% of infants were born with LBW, with lowest rates observed in Rajshahi (11%) and highest rates in Rangpur (28%). Education of mothers (adjusted odds ratio [AOR] 0.52, 95% confidence interval [CI] 0.39–0.68 for secondary or higher educated mother) and poor antenatal care (ANC) (AOR 1.40, 95% CI 1.04–1.90) were associated with LBW after adjusting for mother’s age, parity and cluster effects. Mothers from wealthier families were less likely to give birth to an LBW infant. Further indicators that wealth continues to play a role in LBW were that place of delivery, ANC and delivery assistance by quality health workers were significantly associated with LBW. However there has been a notable fall in LBW prevalence in Bangladesh since the last comparable survey (prevalence 36%), and an evidence of possible elimination of rural/urban disparities.ConclusionsLow birth weight remains associated with key indicators not just of maternal poverty (notably adequate maternal education) but also markers of structural poverty in health care (notably quality ANC). Results based on this sub-sample indicate LBW is still a public health concern in Bangladesh and an integrated effort from all stakeholders should be continued and interventions based on the study findings should be devised to further reduce the risk of LBW.
Background: The rapid growth in cases of COVID-19 has challenged national healthcare capacity, testing systems at an advanced ICU, and public health infrastructure level. This global study evaluates the association between multi-factorial healthcare capacity and case fatality of COVID-19 patients by adjusting for demographic, health expenditure, population density, and prior burden of non-communicable disease. It also explores the impact of government relationships with civil society as a predictor of infection and mortality rates. Methods: Data were extracted from the Johns Hopkins University database, World Bank records and the National Civic Space Ratings 2020 database. This study used data from 86 countries which had at least 1,000 confirmed cases on 30th April 2020. Negative binomial regression model was used to assess the association between case fatality (a ratio of total number of confirmed deaths to total number of confirmed cases) and healthcare capacity index adjusting for other covariates. Findings: Regression analysis shows that greater healthcare capacity was related to lesser case-fatality [incidence rate ratio (IRR) 0.5811; 95% confidence interval (CI) 0.4727-0.7184; p < 0.001] with every additional unit increase in the healthcare capacity index associated with a 42% decrease in the case fatality. Health expenditure and civil society variables did not reach statistical significance but were positively associated with case fatalities. Interpretation: Based on preliminary data, this research suggests that building effective multidimensional healthcare capacity is the most promising means to mitigate future case fatalities. The data also suggests that government's ability to implement public health measures to a degree determines mortality outcomes.
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