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Abstract : Survival Analysis of Duration of Breastfeeding and Associated Factors of Early Cessation of Breastfeeding in Ethiopia
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Abstract: The purpose of this study was to assess the duration of breastfeeding among women of reproductive age in Ethiopia and to identify determinants associated with early cessation of breastfeeding. Data for the study were drawn from the Ethiopia Demographic and Health Survey 2005. The study included mothers of 9,066 children from nine regional states and two city administrations. The Kaplan-Meier and stratified Cox’s hazard model were employed for the analysis of breastfeeding-related data. The Kaplan-Meier survival estimate showed that the probability of mothers who continue to breastfeeding was high (97.3%) for the first month. The breastfeeding rates then declined to 92.5% at 6 months, 78.4% at 12 months, 37% at 24 months and 8.3% at 48 months. The mean and median duration of breastfeeding in Ethiopia were 25.64 and 24.00 months respectively. The stratified Cox regression analysis revealed that younger mothers, mothers who had lived in urban area, mothers having higher education, higher maternal parity, early pregnant and being a Muslim and protestant were significant determinants of early cessation of breastfeeding in Ethiopia. Then, we recommend that the breastfeeding-promotion programs in Ethiopia should give special attention to young mothers, those who lived in urban areas, mothers with higher education, those who have higher parity, those who have early pregnancy and who are Muslims and Protestants since these mothers tend to breastfeed their child for a relatively shorter period of time. Keywords: Breastfeeding duration, Kaplan-Meier estimator, Determinants, Stratified- Cox regression model, Hazard-Ratio, Ethiopia.Download Full Article |
Abstract : The Usefulness of Maximum Daily Temperatures Versus Defined Heatwave Periods in Assessing the Impact of Extreme Heat on ED Admissions for Chronic Conditions
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Abstract: Objective: To compare a heatwave based exposure classification with a maximum daily temperature based exposure classification in assessing the associations between increased heat and emergency department (ED) admissions for chronic conditions. Methods: ED admission data was collected from 4 public hospitals in South Australia from 2007 to 2009. Effects of 5 heatwave periods were examined using conditional logistic regression (heatwave versus non-heatwave) whilst effects of maximum daily temperature were explored using negative binomial regression with temperature classified using <25 °C (reference category) and additional 5 °C increments. Non-linear regression (ED admissions per unit °C) was used to examine possible temperature thresholds for increased ED admissions. Results: In heatwave/non-heatwave analysis, an increased odds of admission during heatwaves was observed for heat-related complaints [OR=3.2; 95%CI=2.5, 4.11] and renal conditions [OR=1.13; 95%CI=1.05, 1.21] only. In temperature based analysis, mental health related conditions began increasing at 30-34 °C compared to <25 °C [IRR=1.11; 95%CI=1.02, 1.20], heat related conditions were increased at 35-39 °C [IRR=3.4; 95%CI=2.48, 4.64] while CVD admissions were lower above 40 °C [IRR=0.89; 95%CI=0.80-0.99]. Significant threshold temperatures were identified for heat-related conditions at 37.6 °C [p<0.001] and for renal admissions at 39.2 °C [p<0.001]. Conclusions: Using maximum daily temperature was a more sensitive approach to detecting effects of heat on ED admissions for chronic disease and also allowed the detection of temperature threshold effects. Assessing the impact of temperature rather than heatwaves should better identify the weather conditions that increase the risk of events amongst individuals with specific chronic conditions. Keywords: Emergency department admissions, excess heat, temperature threshold, chronic conditions, case-cross over design, conditional logistic regression, negative binomial regression.Download Full Article |
Abstract : Survival Analysis of Duration of Breastfeeding and Associated Factors of Early Cessation of Breastfeeding in Ethiopia (11)
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Abstract: The purpose of this study was to assess the duration of breastfeeding among women of reproductive age in Ethiopia and to identify determinants associated with early cessation of breastfeeding. Data for the study were drawn from the Ethiopia Demographic and Health Survey 2005. The study included mothers of 9,066 children from nine regional states and two city administrations. The Kaplan-Meier and stratified Cox’s hazard model were employed for the analysis of breastfeeding-related data. The Kaplan-Meier survival estimate showed that the probability of mothers who continue to breastfeeding was high (97.3%) for the first month. The breastfeeding rates then declined to 92.5% at 6 months, 78.4% at 12 months, 37% at 24 months and 8.3% at 48 months. The mean and median duration of breastfeeding in Ethiopia were 25.64 and 24.00 months respectively. The stratified Cox regression analysis revealed that younger mothers, mothers who had lived in urban area, mothers having higher education, higher maternal parity, early pregnant and being a Muslim and protestant were significant determinants of early cessation of breastfeeding in Ethiopia. Then, we recommend that the breastfeeding-promotion programs in Ethiopia should give special attention to young mothers, those who lived in urban areas, mothers with higher education, those who have higher parity, those who have early pregnancy and who are Muslims and Protestants since these mothers tend to breastfeed their child for a relatively shorter period of time. Keywords: Breastfeeding duration, Kaplan-Meier estimator, Determinants, Stratified- Cox regression model, Hazard-Ratio, Ethiopia.Download Full Article |
Abstract : Survival Analysis of Duration of Breastfeeding and Associated Factors of Early Cessation of Breastfeeding in Ethiopia (12)
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Abstract: The purpose of this study was to assess the duration of breastfeeding among women of reproductive age in Ethiopia and to identify determinants associated with early cessation of breastfeeding. Data for the study were drawn from the Ethiopia Demographic and Health Survey 2005. The study included mothers of 9,066 children from nine regional states and two city administrations. The Kaplan-Meier and stratified Cox’s hazard model were employed for the analysis of breastfeeding-related data. The Kaplan-Meier survival estimate showed that the probability of mothers who continue to breastfeeding was high (97.3%) for the first month. The breastfeeding rates then declined to 92.5% at 6 months, 78.4% at 12 months, 37% at 24 months and 8.3% at 48 months. The mean and median duration of breastfeeding in Ethiopia were 25.64 and 24.00 months respectively. The stratified Cox regression analysis revealed that younger mothers, mothers who had lived in urban area, mothers having higher education, higher maternal parity, early pregnant and being a Muslim and protestant were significant determinants of early cessation of breastfeeding in Ethiopia. Then, we recommend that the breastfeeding-promotion programs in Ethiopia should give special attention to young mothers, those who lived in urban areas, mothers with higher education, those who have higher parity, those who have early pregnancy and who are Muslims and Protestants since these mothers tend to breastfeed their child for a relatively shorter period of time. Keywords: Breastfeeding duration, Kaplan-Meier estimator, Determinants, Stratified- Cox regression model, Hazard-Ratio, Ethiopia.Download Full Article |
Abstract: A Comparison of Parametric and Semi-Parametric Models for Microarray Data Analysis
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Abstract: Microarray technology has revolutionized genomic studies by enabling the study of differential expression of thousands of genes simultaneously. Parametric, nonparametric and semi-parametric statistical methods have been proposed for gene selection within the last sixteen years. In an effort to find the “gold standard", the performance of some common parametric and nonparametric methods have been compared in terms of power to select differentially expressed genes and other desirable properties. However, no such comparisons have been conducted between parametric and semi-parametric models. In this study, we compared a semi-parametric model based on copulas with a parametric model (the quantitative trait analysis or QTA model) in terms of power and the ability to control the Type I error rate. In addition, we proposed a simple algorithm for choosing an optimal copula. The two approaches were applied to a publicly available melanoma cell lines dataset for validation. Both methods performed well in terms of power but the copula approach was notably the better. In terms of the Type I error rate control, the two methods were comparable. More methods for selecting an optimal copula for gene expression data need to be developed, as the proposed procedure is limited to copulas that permit both negative and positive dependence only. Keywords: Copula, Goodness-of-fit, Melanoma, Microarray, Power, Type I error. |