scholarly journals Cesarean delivery and early childhood diseases in Bangladesh: An analysis of Demographic and Health Survey (BDHS) and Multiple Indicator Cluster Survey (MICS)

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242864
Author(s):  
Mohammad Nayeem Hasan ◽  
Muhammad Abdul Baker Chowdhury ◽  
Jenifar Jahan ◽  
Sumyea Jahan ◽  
Nasar U. Ahmed ◽  
...  
Keyword(s):  
Early Childhood ◽  
Cesarean Delivery ◽  
Health Survey ◽  
Negative Impact ◽  
Childhood Diseases ◽  
Childhood Disease ◽  
Multiple Indicator Cluster Survey ◽  
Confounding Variables ◽  
Multiple Indicator ◽  
Size At Birth

Introduction The rate of cesarean delivery (C-section) has been increasing worldwide, including Bangladesh, and it has a negative impact on the mother and child's health. Our aim was to examine the association between C-section and childhood diseases and to identify the key factors associated with childhood diseases. Methods We used four nationally representative data sets from multiple indicator cluster survey (MICS, 2012 and 2019) and Bangladesh Demographic and Health Survey (BDHS, 2011and 2014) and analyzed 25,270 mother-child pairs. We used the frequency of common childhood diseases (fever, short or rapid breaths, cough, blood in stools, and diarrhea) as our outcome variable and C-section as exposure variable. We included mother’s age, place of residence, division, mother’s education, wealth index, child age, child sex, and child size at birth as confounding variables. Negative binomial regression model was used to analyze the data. Results In the BDHS data, the prevalence of C-section increased from 17.95% in 2011 to 23.33% in 2014. Also, in MICS, the prevalence almost doubled over an eight-year period (17.74% in 2012 to 35.41% in 2019). We did not observe any significant effect of C-section on childhood diseases in both surveys. Only in 2014 BDHS, we found that C-section increases the risk of childhood disease by 5% [Risk Ratio (RR): 1.05, 95% CI: 0.95, 1.17, p = 0.33]. However, the risk of childhood disease differed significantly in all survey years by division, child's age, and child’s size at birth after adjusting for important confounding variables. For example, children living in Chittagong division had a higher risk [(2011 BDHS RR: 1.22, 95% CI: 1.08, 1.38) and (2019 MICS RR: 1.21, 95% CI: 1.08, 1.35)] of having disease compared to Dhaka division. Maternal age, education, and wealth status showed significant differences with the outcome in some survey years. Conclusion Our study shows that C-section in Bangladesh continued to increase over time, and we did not find significant association between C-section and early childhood diseases. High C-section rate has a greater impact on maternal and child health as well as the burden on the health care system. We recommend raising public awareness of the negative impact of unnecessary C-section in Bangladesh.

scholarly journals The Role of Sociodemographic and Psychosocial Variables in Early Childhood Development: A Secondary Data Analysis of the 2014 Multiple Indicator Cluster Survey in the Dominican Republic

2021 ◽  
Author(s):  
Laura V. Sánchez-Vincitore ◽  
Arachu Castro
Keyword(s):  
Early Childhood ◽  
Dominican Republic ◽  
Early Childhood Development ◽  
Childhood Development ◽  
Developmental Potential ◽  
Cluster Survey ◽  
Multiple Indicator Cluster Survey ◽  
Psychosocial Model ◽  
Multiple Indicator ◽  
At Home

AbstractIntroductionThe association between sociodemographic factors, such as poverty, lack of maternal schooling, and being male at birth, and childhood developmental delay and poor educational outcomes has been established in the Dominican Republic. However, moderating factors present or introduced in families to buffer the effects of such factors on childhood development are still unknown.MethodsWe conducted a secondary analysis of the 2014 Multiple Indicator Cluster Survey for the Dominican Republic, a national household survey focused on maternal and child health and development. The first aim of our study was to determine if a sociodemographic model predicted early childhood development. The second aim was to determine if a psychosocial model (including family childrearing practices, discipline, and early childhood stimulation) predicted early childhood development above and beyond the sociodemographic model.ResultsWe found that both models predicted childhood development significantly, but that the psychosocial model explained 5% more variance than the sociodemographic model. The most relevant sociodemographic predictors were socioeconomic position and mother’s education, which uniquely explained 21% and 17% of the early childhood development variance, respectively. The most salient psychosocial predictors of early childhood development were: 1) attendance to an early childhood education program, which uniquely explained 15.0% of the variance; 2) negative discipline, which uniquely explained 12.4% (negative impact); 3) the number of children’s books at home, which uniquely explained 12.0%; and 4) stimulating activities at home, which uniquely explained 5%.ConclusionThese results have multiple implications for social programs that aim to improve children’s developmental potential in contexts of poverty. Although the results show a protective effect of psychosocial factors, sustainable and large-scale intervention should not be limited to just buffering effects, but to actually solve the underlying problem which is that poverty prevents children from reaching their developmental potential.

scholarly journals Risk factors for early childhood disability in Bangladesh: Evidence from Multiple Indicator Cluster Survey 2019

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259532
Author(s):  
Shilpi Rani Saha ◽  
Md. Mobarak Hossain Khan
Keyword(s):  
Early Childhood ◽  
Human Life ◽  
Policy Formulation ◽  
Community Level ◽  
Categorical Variables ◽  
Childhood Disability ◽  
Public Health Burden ◽  
Cluster Survey ◽  
Multiple Indicator Cluster Survey ◽  
Multiple Indicator

Introduction Early childhood is a vital part of human life because most of the brain developments occur in this particular period. Early childhood disability is a significant global public health burden, which can negatively impact the children’s quality of life and their overall productivity. It is also a major social and economic problem in Bangladesh. Therefore, it is very important to understand the associated factors for early childhood disability, which may help disability prevention, better management and policy formulation. The main objective of this study is to investigate the child, family, and community-level factors associated with early childhood disability in Bangladesh. Methods A cross sectional nationally representative data was derived from Multiple Indicator Cluster Survey (MICS), 2019. A total of 14,072 Bangladeshi children under five years of age were selected for this study. Various types of statistical analysis (simple, bivariate, multivariable) were performed. To assess the bivariate relationship between chosen categorical variables (independent) and early childhood disability (dependent), a chi-square test was used. The multivariable ordinal logistic regression was used to find out the association of disability with child, family, and community-level factors. Results The results show that 2.0% of the children have at least one disability and 0.8% have more disabilities. Several factors namely not attending in early childhood education [Odds Ratio (OR) = 0.65; 95% confidence interval (CI) = 0.13–1.17 Ρ = 0.01], having mother’s functional difficulty (OR = 1.23; 95% (CI) = 0.58–1.88 Ρ <0.001), unhappy mother’s life (OR = 0.85; 95% CI = 0.30–1.39 Ρ <0.001), parents without internet access (OR = 0.68; 95% CI = 0.06–1.29 Ρ = 0.03) and parents using mobile phone (OR = 0.52; 95% CI = 0.09–0.95 Ρ = 0.02) were found to be important for early childhood disability in Bangladesh. Conclusion Early childhood disability is still neglected in Bangladesh and further epidemiological studies are recommended. The findings of this study may help policy makers and relevant stakeholders to develop interventions for reducing the overall burden of early childhood disability.

scholarly journals Decision Support System for Classification of Early Childhood Diseases Using Principal Component Analysis and K-Nearest Neighbors Classifier

2019 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Damar Dananjaya ◽  
Indah Werdiningsih ◽  
Rini Semiati
Keyword(s):  
Principal Component Analysis ◽  
Early Childhood ◽  
Nearest Neighbor ◽  
Principal Component ◽  
Component Analysis ◽  
Major Influence ◽  
K Nearest Neighbor ◽  
Childhood Diseases ◽  
Childhood Disease

Background: Data on early childhood disease collected in clinics has accumulated into big data. Those data can be used for classification of early childhood diseases to help medical staff in diagnosing diseases that attack early childhoods.Objective: This study aims to apply Principal Component Analysis (PCA) and K-Nearest Neighbor (K-NN) Classifier for the classification of early childhood diseases.Methods: Data analysis was performed using PCA to obtain variables that had a major influence on the classification of early childhood diseases. PCA was done by observing the correlation between variables and eliminating variables that have little influence on classification. Furthermore, data on early childhood disease was classified using the K-Nearest Neighbor Classifier method.Results:  The results of system evaluation using 150 test data indicated that the classification system by applying PCA and KNN Classifier had an accuracy value of 86%.Conclusion: PCA can be used to reduce the number of variables involved so that it can improve system performance in terms of efficiency. In addition, the application of PCA and KNN can also improve accuracy in the classification of early childhood diseases.

ASSOCIATION OF SOCIO-DEMOGRAPHIC FACTORS WITH DIARRHEA IN CHILDREN LESS THAN FIVE YEARS: A SECONDARY ANALYSIS OF MULTIPLE INDICATOR CLUSTER SURVEY SINDH 2014

1970 ◽  
Vol 7 (2) ◽  
pp. 85-89
Author(s):  
Muhammad Irfan ◽  
Syed Mustansir Hussain Zaidi ◽  
Hira Fatima Waseem
Keyword(s):  
Rural Areas ◽  
Demographic Factors ◽  
Wealth Index ◽  
Household Wealth ◽  
Cluster Survey ◽  
Multiple Indicator Cluster Survey ◽  
Increased Risk ◽  
Multiple Indicator ◽  
Mother Education ◽  
Socio Demographic Factors

Background: Diarrhea founds to be the major cause of morbidity and mortality in children less than five years. Various factors are associated with diarrhea but socio-demographic factors are the main key elements, which associated with diarrhea. Methods: This study was examined association of socio-demographic factors with diarrhea in children less than five years of age of Sindh, Pakistan, using data from the Multiple Indicator Cluster Survey (MICS) conducted from January 2014 to August 2014. Data were collected for 18,108 children in whom 16,449 children had complete data of demographic variables being included in the analysis. Bivariate analysis was done using Pearson's Chi square test and multivariate analysis being done using binary logistic regression. Results: We found increased risk of diarrhea among children lives in rural areas while household wealth index quintile was also associated with diarrhea. Children in the poor, middle and fourth wealth index quintiles being at increased risk of diarrhea compared to children in the richest wealth index quintile. The highest risk of diarrhea was found for the child having mother with no education as well as children aged 12-23 months. Conclusion: Age of child, mother education and wealth index found significant with diarrhea while Male children, child aged 12-23 months, child with no mother education, child from rural areas and child from poor households found with high risk of diarrhea.

scholarly journals Sociodemographic factors and early marriage among women in Bangladesh, Ghana and Iraq: An illustration from Multiple Indicator Cluster Survey

Heliyon ◽  
2021 ◽  
Vol 7 (5) ◽  
pp. e07111
Author(s):  
Ahmed Abdus Saleh Saleheen ◽  
Sharmin Afrin ◽  
Samia Kabir ◽  
Md. Jakaria Habib ◽  
Maliha Afroj Zinnia ◽  
...  
Keyword(s):  
Sociodemographic Factors ◽  
Early Marriage ◽  
Cluster Survey ◽  
Multiple Indicator Cluster Survey ◽  
Multiple Indicator

scholarly journals Correlates of child functional difficulties status in Ghana: A further analysis of the 2017/18 multiple indicator cluster survey

Heliyon ◽  
2020 ◽  
Vol 6 (12) ◽  
pp. e05727
Author(s):  
Nutifafa Eugene Yaw Dey ◽  
Emmanuel Dziwornu ◽  
Kwabena Frimpong-Manso ◽  
Henry Ofori Duah ◽  
Pascal Agbadi
Keyword(s):  
Cluster Survey ◽  
Functional Difficulties ◽  
Multiple Indicator Cluster Survey ◽  
Multiple Indicator

scholarly journals Early Childhood Educators’ Wellbeing During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Patricia Eadie ◽  
Penny Levickis ◽  
Lisa Murray ◽  
Jane Page ◽  
Catriona Elek ◽  
...  
Keyword(s):  
Early Childhood ◽  
Lower Risk ◽  
Online Survey ◽  
Negative Impact ◽  
Linear Regression Analysis ◽  
Organizational Structures ◽  
Research Network ◽  
Student Teacher Relationship ◽  
Learning At Home ◽  
The Impact

AbstractThe importance of Early Childhood (EC) educators’ wellbeing has been brought into sharp focus during the COVID-19 pandemic, as educators have navigated numerous additional stressors while providing education and care services for some children and ongoing support for many others learning at home. This study aimed to explore the impact of the pandemic on EC educators’ wellbeing and educator-child relationships, as growing evidence shows the influence of these factors on children’s developmental outcomes.In July 2020, members of a Research Network of EC Professionals—who previously identified educator wellbeing as a priority issue—were invited to participate in an online survey. The survey included two published, validated scales: the Early Childhood Professional Wellbeing scale (ECPW) and the Student–Teacher Relationship Scale (modified). Survey items about educators’ experiences during the pandemic were also included. Two hundred and thirty-two EC educators from across Australia completed the survey, mostly from Victoria where lockdowns were most severe. Linear regression analysis demonstrated stronger professional wellbeing was associated with less conflict in educator-child relationships and lower risk of staff turnover. This was more likely to be experienced by senior or more experienced staff. Although a negative impact of COVID-19 was reported, ECPW scores were relatively high, and organizational structures supporting professional wellbeing were most strongly associated with lower risk of turnover (r = 0.63, p < 0.001). Findings highlight that supporting EC educators’ wellbeing is essential for workforce retention, and for promoting quality educator-child relationships which are central to young children’s learning and development.

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