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Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
by
Das, Sumonkanti
, Rahman, Rajwanur M
in
Age Factors
/ Anthropometric index
/ Anthropometry
/ Bangladesh
/ Bangladesh - epidemiology
/ Binary logistic regression model
/ Birth Intervals
/ Body Weight
/ Child malnutrition
/ child nutrition
/ Child Nutrition Disorders
/ Child Nutrition Disorders - diagnosis
/ Child Nutrition Disorders - epidemiology
/ Child, Preschool
/ children
/ Children & youth
/ Clinical Nutrition
/ diagnosis
/ Diarrhea
/ Educational Status
/ epidemiology
/ Female
/ Fever
/ Health Promotion and Disease Prevention
/ household income
/ Human nutrition
/ Humans
/ Infant
/ Infant, Newborn
/ Logistic Models
/ logit analysis
/ Malnutrition
/ Malnutrition in children
/ maternal nutrition
/ Maternal Welfare
/ Medical research
/ Medicine
/ Medicine & Public Health
/ mothers
/ Nutrition
/ Nutritional Status
/ Ordinal logistic regression model
/ Partial proportional odds model
/ parturition
/ Proportional odds model
/ Regression analysis
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Studies
/ Surveys
2011
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Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
by
Das, Sumonkanti
, Rahman, Rajwanur M
in
Age Factors
/ Anthropometric index
/ Anthropometry
/ Bangladesh
/ Bangladesh - epidemiology
/ Binary logistic regression model
/ Birth Intervals
/ Body Weight
/ Child malnutrition
/ child nutrition
/ Child Nutrition Disorders
/ Child Nutrition Disorders - diagnosis
/ Child Nutrition Disorders - epidemiology
/ Child, Preschool
/ children
/ Children & youth
/ Clinical Nutrition
/ diagnosis
/ Diarrhea
/ Educational Status
/ epidemiology
/ Female
/ Fever
/ Health Promotion and Disease Prevention
/ household income
/ Human nutrition
/ Humans
/ Infant
/ Infant, Newborn
/ Logistic Models
/ logit analysis
/ Malnutrition
/ Malnutrition in children
/ maternal nutrition
/ Maternal Welfare
/ Medical research
/ Medicine
/ Medicine & Public Health
/ mothers
/ Nutrition
/ Nutritional Status
/ Ordinal logistic regression model
/ Partial proportional odds model
/ parturition
/ Proportional odds model
/ Regression analysis
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Studies
/ Surveys
2011
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Do you wish to request the book?
Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
by
Das, Sumonkanti
, Rahman, Rajwanur M
in
Age Factors
/ Anthropometric index
/ Anthropometry
/ Bangladesh
/ Bangladesh - epidemiology
/ Binary logistic regression model
/ Birth Intervals
/ Body Weight
/ Child malnutrition
/ child nutrition
/ Child Nutrition Disorders
/ Child Nutrition Disorders - diagnosis
/ Child Nutrition Disorders - epidemiology
/ Child, Preschool
/ children
/ Children & youth
/ Clinical Nutrition
/ diagnosis
/ Diarrhea
/ Educational Status
/ epidemiology
/ Female
/ Fever
/ Health Promotion and Disease Prevention
/ household income
/ Human nutrition
/ Humans
/ Infant
/ Infant, Newborn
/ Logistic Models
/ logit analysis
/ Malnutrition
/ Malnutrition in children
/ maternal nutrition
/ Maternal Welfare
/ Medical research
/ Medicine
/ Medicine & Public Health
/ mothers
/ Nutrition
/ Nutritional Status
/ Ordinal logistic regression model
/ Partial proportional odds model
/ parturition
/ Proportional odds model
/ Regression analysis
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Studies
/ Surveys
2011
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Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
Journal Article
Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh
2011
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Overview
Background
The study attempts to develop an ordinal logistic regression (OLR) model to identify the determinants of child malnutrition instead of developing traditional binary logistic regression (BLR) model using the data of Bangladesh Demographic and Health Survey 2004.
Methods
Based on weight-for-age anthropometric index (Z-score) child nutrition status is categorized into three groups-severely undernourished (< -3.0), moderately undernourished (-3.0 to -2.01) and nourished (≥-2.0). Since nutrition status is ordinal, an OLR model-proportional odds model (POM) can be developed instead of two separate BLR models to find predictors of both malnutrition and severe malnutrition if the proportional odds assumption satisfies. The assumption is satisfied with low p-value (0.144) due to violation of the assumption for one co-variate. So partial proportional odds model (PPOM) and two BLR models have also been developed to check the applicability of the OLR model. Graphical test has also been adopted for checking the proportional odds assumption.
Results
All the models determine that age of child, birth interval, mothers' education, maternal nutrition, household wealth status, child feeding index, and incidence of fever, ARI & diarrhoea were the significant predictors of child malnutrition; however, results of PPOM were more precise than those of other models.
Conclusion
These findings clearly justify that OLR models (POM and PPOM) are appropriate to find predictors of malnutrition instead of BLR models.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Binary logistic regression model
/ Child Nutrition Disorders - diagnosis
/ Child Nutrition Disorders - epidemiology
/ children
/ Diarrhea
/ Female
/ Fever
/ Health Promotion and Disease Prevention
/ Humans
/ Infant
/ Medicine
/ mothers
/ Ordinal logistic regression model
/ Partial proportional odds model
/ Studies
/ Surveys
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