scholarly journals Bivariate binary analysis on composite index of anthropometric failure of under-five children and household wealth-index

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Demeke Lakew Workie ◽  
Lijalem Melie Tesfaw
Keyword(s):  
Logistic Regression ◽  
Composite Index ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Household Wealth ◽  
Education Level ◽  
Multiple Birth ◽  
Under Five ◽  
Under Five Children ◽  
Study Results

Abstract Background Malnutrition is the most common cause of mortality and morbidity of children in low and middle income countries including Ethiopia and household wealth index shares the highest contribution. Thus, in this study it is aimed to conduct bivariate binary logistic regression analysis by accounting the possible dependency of child composite index anthropometric failure and household wealth index. Methods In this study the data from Ethiopian Demographic and Health Survey (EDHS) 2016 involved 9411 under five children was considered. Child Composite Index Anthropometric Failure (CIAF) measures the aggregate child undernourished derived from the conventional anthropometric indices (stunting, underweight and wasting). The correlation between CIAF and wealth index was checked and significant correlation found. To address the dependency between the two outcome variables bivariate binary logistic regression was used to analyze the determinants of child CAIF and household wealth index jointly. Results Study results show that region, place of residence, religion, education level of women and husband/partner, sex of child, source of drinking water, household size and number of under five children in the household, mothers body mass index, multiple birth and anemia level of child had significant association with child CIAF. Female children were 0.82 times less likely to be CIAF compared to male and multiple birth children were more likely to be CIAF compared to single birth. Children from Oromia, Somalie, Gambela, SNNPR, Harari and Addis Ababa region were 0.6, 0.56, 0.67, 0.52, 0.6 and 0.44 times less likely to be CIAF compared to Tigray. A household from rural area were 15.49 times more likely poor compared to a household. The estimated odds of children whose mothers attended primary, and secondary and higher education was 0.82, and 0.52 times respectively the estimated odds of children from mothers who had never attended formal education. Conclusion The prevalence of children with composite index anthropometric failure was high and closely tied with the household wealth index. Among the determinants, region, religion, family education level, and anemia level of child were statistically significant determinants of both CIAF and household wealth index. Thus, the authors recommend to concerned bodies and policymakers work on household wealth index to reduce the prevalence of child composite anthropometric failure.

scholarly journals Multivariate logistic regression analysis on the association between anthropometric indicators of under-five children in Nigeria: NDHS 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lijalem Melie Tesfaw ◽  
Haile Mekonnen Fenta
Keyword(s):  
Logistic Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Well Being ◽  
Household Wealth ◽  
Multiple Birth ◽  
Age At First Birth ◽  
Multivariate Logistic Regression ◽  
Under Five ◽  
Anthropometric Indicators ◽  
Under Five Children

Abstract Background Child malnutrition is a huge health problem having multifaceted consequences for child survival and long-term well-being. Although, several studies investigated stunting, underweight, and wasting in low- and middle-income countries, in Nigeria, the link between them received little attention. The aim of this study is, therefore, to assess the association between anthropometric indicators of under-five children such as stunting, underweight and wasting given that of other characteristics of children and households. Methods The data for this study was obtained from Nigerian Demographic and health survey (NDHS) in 2018. A total of 11,314 under-five children were involved. Multivariate logistic regression model was used to determine the association between stunting, underweight and wasting given that of the estimated effect of other determinants. Results From 11,314 under-five children the study considered 36.2, 21.4 and 6.7% of them suffered from stunting, underweight and wasting, respectively. About half (50.7%) of the children were male, 24.1% was obtained from North West region of Nigeria, and 37.8% of them were from households having unimproved drinking water. The pairwise dependency between stunting and underweight; underweight and wasting was measured using odds ratio (OR) of 15.796, and 16.750 respectively. The estimated odds of children from richest household to become stunted, underweight, and wasted was respectively 0.392, 0.540, 0.786 times that of the estimated odds of children from poorest households. Conclusion The prevalence of under-five children with stunting, underweight and/or wasting in Nigeria was very high. The important determinants of stunting, underweight, and wasting for under five children were household wealth index, women body mass index, sex of the child, anemia, mothers’ age at first birth, and a diarrhea two weeks prior to the survey. Whereas, region, religion, multiple birth, women’s educational level significantly associated with both stunting and underweight. Both stunting and wasting significantly associated with underweight.

scholarly journals Bayesian Multilevel Analysis of Determinants of Acute Respiratory Infection in Children under the Age of Five Years in Ethiopia

2020 ◽  
Author(s):  
Amanuel Merera ◽  
Tilahun Asena ◽  
Mebratu Senbeta
Keyword(s):  
Drinking Water ◽  
Vitamin A ◽  
Respiratory Infection ◽  
Prevalence Rate ◽  
Acute Respiratory Infection ◽  
Wealth Index ◽  
Household Wealth ◽  
Children Under Five ◽  
Under Five ◽  
Under Five Children

Abstract Background: Acute respiratory tract infection (ARI) is a leading cause of morbidity and mortality in children under the age of five years in the world. ARIs, principally pneumonia, account for approximately 1.9 million (1.6 - 2.2 million) deaths globally in children under the age of five years in Ethiopia. Among these deaths majority occur in the developing world. The share for low and middle-income countries takes the highest indeed. In Ethiopia, the prevalence rate of ARI was 7% according to 2016 EDHS estimates. Method: Bayesian multilevel approach was employed to assess possible factors associated with the prevalence of acute respiratory infection (ARI) among under-five children in Ethiopia. The data was collected from 10,641 children under the age of five years out of which 9,918 children were considered in this study. Result: The ARI prevalence rate for children under five years was estimated as 8.4%, which was slightly higher than the estimated prevalence level of the country. The highest proportion of the prevalence of ARI was observed for children whose mothers had no education. The major health, environmental and nutritional related background characteristics of the proportion of children who had ARI varied from one region to another. The highest prevalence of ARI was observed in Tigray (15.31%) followed by Oromia (14.40%) as opposed to the low prevalence which was recorded in Benishangul Gumuz (2.58%). The utilization of vitamin A was analyzed and the results shows that about 43.10% who received vitamin A had the lowest proportion on the prevalence of ARI (7.75%) compared to not having vitamin A. About 11.13% of under-five children had Diarrhea with the highest prevalence of ARI (24.64%) and the highest prevalence of ARI was observed for the child whose source of drinking water were unprotected/unimproved (9.39%). Conclusion: The age of the child, household wealth index, mother educational level, and vitamin A supplement, history of diarrhea, maternal work, stunting and source of drinking water were found to be significantly affecting the prevalence of ARI among children under five years. Furthermore, the study revealed that there is a significant variation of incidence of ARI between and within the regions of Ethiopia. Attention should be given to those predictor variables while planning to increase the health status of children in Ethiopia.

scholarly journals Tracking Progress in Anthropometric Failure Among Under-five Children in Ethiopia: A Geospatial and Multilevel Analysis.

2020 ◽  
Author(s):  
Binyam Tariku Seboka ◽  
Samuel Hailegebreal ◽  
Delelegn Emwodew Yehualashet ◽  
Abel Desalegn Demeke
Keyword(s):  
Logistic Regression ◽  
Associated Factors ◽  
Composite Index ◽  
Temporal Distribution ◽  
Health Concern ◽  
Multilevel Logistic Regression ◽  
Statistical Tool ◽  
Under Five ◽  
Under Five Children ◽  
Under Nutrition

Abstract Background Under-nutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. Additionally, this study provides a Spatio-temporal distribution and associated factors of childhood anthropometric failures across time.Methods Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0-59 months, which is a nationally representative sample in Ethiopia. Analytical methods used in this paper include multivariate multilevel logistic regression to identify associated factors and Getis-Ord spatial statistical tool to identify high and low hotspots areas of anthropometric failures. ResultThe prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5%, 51%, and 46.2% of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education. Conclusion In addition to identifying wasted, stunted, and overweight children, CIAF also identified children with multiple conditions, which are generally neglected in most nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The identified socio-demographic characteristics and districts at an increased likelihood of anthropometric failure can inform localized intervention and prevention strategies to improve the nutritional status and healthcare of children in Ethiopia.

scholarly journals Tracking progress in anthropometric failure among under-five children in Ethiopia: a geospatial and multilevel analysis

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Binyam Tariku Seboka ◽  
Samuel Hailegebreal ◽  
Delelegn Emwodew Yehualashet ◽  
Abel Desalegn Demeke
Keyword(s):  
Logistic Regression ◽  
Formal Education ◽  
Composite Index ◽  
Temporal Distribution ◽  
Secondary Data ◽  
Health Concern ◽  
Multilevel Logistic Regression ◽  
Under Five ◽  
Under Five Children ◽  
Under Nutrition

Abstract Background Undernutrition is a major public health concern among under-five children in many developing countries. This work evaluated the overall prevalence of under-nutrition by using a composite index of anthropometric failure (CIAF), which helps in the detection of children with multiple anthropometric failures. This research also includes the Spatio-temporal distribution of childhood anthropometric failures across time. Methods Secondary data was obtained from the Ethiopian Demographic and Health Survey for the survey 2005, 2011, and 2016 years. Data included 23,864 samples of children between the ages of 0–59 months, which is a nationally representative sample in Ethiopia. Other than descriptive statistics, the multivariate multilevel logistic regression was used to identify associated factors, and Getis-Ord spatial statistical tools were employed to identify high and low hotspots areas of anthropometric failures. Result The prevalence obtained with CIAF in 2005, 2011, and 2016 was, 53.5 %, 51 %, and 46.2 % of children were suffering from under-nutrition respectively. The spatial analysis revealed areas that are at a higher risk of anthropometric failures consistently were found in northern parts of the country, largely in the Amhara, Tigray, and Afar regions. Multilevel logistic regression analysis showed that the risk of anthropometric failure was higher among older children, had low birth weight, had a mother with low BMI, was in a rural area, had mothers and fathers without formal education. Conclusions In addition to identifying wasted, stunted, and underweight children, CIAF also identified children with multiple conditions, which are often overlooked in nutritional surveys. As revealed by this composite index, the prevalence of anthropometric failure remains considerably high and its spatial distribution also significantly varied across the regions in the country. The established socio-demographic characteristics and districts with a higher risk of anthropometric failure can be used to develop localized intervention and prevention strategies to improve Ethiopian children’s nutritional status and healthcare.

scholarly journals Pemodelan Determinan Pernikahan Dini di Daerah Pedesaan dengan Pendekatan Regresi Logistik Biner

2021 ◽  
Vol 4 (2) ◽  
pp. 76
Author(s):  
Aloysius Bela Boro ◽  
Siskarossa Ika Oktora
Keyword(s):  
Logistic Regression ◽  
Rural Areas ◽  
Goodness Of Fit ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Early Marriage ◽  
Negative Effects ◽  
Response Variable ◽  
Study Results ◽  
The Government

<p><strong>A</strong><strong>bstract</strong><strong>.</strong> The behavior of early marriage in Indonesia is still high and most prevalent in rural areas. In addition to violating the law, a marriage performed before reaching 19 years also has many negative effects. One of them is the death of the mother and the baby. Using data from the Demographic and Health Survey 2017, this study aims to analyze the determinants of early marriages in rural areas in Indonesia. The response variable used is binary categorical data, namely the status of early marriage and not early marriage, so we use a binary logistic regression. The steps performed on this model include estimates of parameters, parameter testing either simultaneously or partially, and a test of the goodness of fit. The results show that the variables of education level, internet access, and wealth index significantly affected early marriage status in rural areas in Indonesia in 2017. Based on the goodness of fit result, this model is proper for modeling early marriage behavior in Indonesia. The study results can be used as a reference for the government in formulating policies to overcome the problem of early marriage in rural areas in Indonesia.</p><p> <strong>Keywords</strong><strong>: </strong>early marriage, rural area, categorical response variable, binary logistic regression</p>

scholarly journals Spatial Prevalence and Determinants of Malaria among under-five Children in Ghana

2021 ◽  
Author(s):  
Bedilu Alamirie Ejigu ◽  
Eshetu Wencheko
Keyword(s):  
Rural Areas ◽  
Hot Spot ◽  
Control Program ◽  
Wealth Index ◽  
Household Wealth ◽  
Malaria Prevalence ◽  
Vulnerable Groups ◽  
Eastern Region ◽  
Under Five ◽  
Under Five Children

AbstractIn Ghana malaria is an endemic disease and the incidence of malaria still accounts for 38.0% of all outpatient attendance with the most vulnerable groups being children under 5 years of age. In order to alleviate this problem, it is essential to design geographically targeted and cost-effective intervention mechanisms guided by up-to-date and reliable data and maps that show the spatial prevalence of the disease. The 2016 Ghana Malaria Indicator Survey data (N = 2,910 under-five children) were analyzed using model-based geostatistical methods with the two objectives to: (1) explore individual-, household-, and community-level determinant variables associated with malaria illness in U5 children, and (2) produce prevalence maps of malaria across the study locations in the country. The overall weighted prevalence of malaria by microscopy blood smear and rapid diagnostic tests were 20.63% (with 95% CI: 18.85% - 22.53%) and 27.82% (with 95% CI: 25.81% - 29.91%), respectively. Across regions of Ghana, the prevalence of malaria ranges from 5% in Greater Accra to 31% in Eastern region. Malaria prevalence was higher in rural areas, increased with child age, and decreased with better household wealth index and higher level of mother’s education. Given the high prevalence of childhood malaria observed in Ghana, there is an urgent need for effective and efficient public health interventions in hot spot areas. The determinant variables of malaria infection that have been identified in this study as well as the maps of parasitaemia risk could be used in malaria control program implementation to define priority intervention areas.

scholarly journals Trends and Predictors of underweight among under-five children in Ethiopia, based on Ethiopian Demographic and Health Survey 2005 -2016. Multivariable Decomposition analysis

2020 ◽  
Author(s):  
Tilahun Yemanu Birhan ◽  
Dessie Abebaw Angaw
Keyword(s):  
Parental Education ◽  
Research Question ◽  
Decomposition Analysis ◽  
Wealth Index ◽  
Household Wealth ◽  
Demographic And Health Surveys ◽  
Data Set ◽  
Under Five ◽  
Under Five Children ◽  
Duration Of Breastfeeding

Abstract Background Underweight is one of the paramount major worldwide health problems, and it touches a large number of population from infancy to old age. This study aimed to analyze the trends and predictors of change in underweight among under-five children in Ethiopia Method The data for this study were accessed from three Ethiopian Demographic and Health Surveys data set 2005, 2011 and 2016. The trend was examined separately for the periods 2005–2011, 2005-2016, and 2011-2016. Multivariate decomposition analysis of change in underweight was employed to answer the major research question of this study. The technique employed the output from the logistic regression model to parcel out the observed difference in underweight into components, and STATA 14 was utilized for data management and analysis. Result Among children in Ethiopia the prevalence of underweight declined from 38% in 2005 to 25% in 2016. The decomposition analysis indicated that almost half of the overall change in underweight was due to difference in characteristics. Change in the composition of parental education, wealth index, duration of breastfeeding, respondents’ occupation, was the major contributor for the decline of underweight, while the age of child and presence of diarrhea were contributors for the rise of underweight in Ethiopia. Conclusion underweight shows a remarkable decline over the last decades in Ethiopia. Change in composition of Birth size, duration of breastfeeding, household wealth quantile (richer) and husband/partner primary education are attributable to the decline of underweight.

scholarly journals Hand washing practice at critical times and its associated factors among mothers of under five children in Debark town, northwest Ethiopia, 2018

2019 ◽  
Vol 45 (1) ◽  
Author(s):  
Henok Dagne ◽  
Laekemariam Bogale ◽  
Muluneh Borcha ◽  
Anley Tesfaye ◽  
Baye Dagnew
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Associated Factors ◽  
Binary Logistic Regression ◽  
Hand Washing ◽  
Binary Logistic Regression Analysis ◽  
Under Five ◽  
Under Five Children ◽  
Critical Times

Abstract Background The burden of communicable diseases within developing countries is mainly influenced by poor personal hygiene practices. Hand washing is considered as most cost effective intervention for reducing health problems such as diarrhoea and acute respiratory tract infections. This study aimed to assess hand washing practice at critical times and identify associated factors among mothers of under five children in Debark town. Method A community based cross-sectional study design was carried out from May 1–20, 2018 in Debark town. After selection of participants using simple random sampling, face to face interview was performed by using semi-structured pre-tested questionnaire. Data were entered into EPI Info 7 and exported into SPSS 21 for further analysis. Results were presented by simple frequency, percentage and mean for descriptive variables. Binary logistic regression analysis was used to test the association of dependent and independent factors. Variables with 95% confidence interval and p ≤ 0.2 during the univariable binary logistic regression analysis were included in the multivariate logistic regression analysis. At the final model variables with p ≤ 0.05 were treated as significantly associated factors of hand washing practice at critical times. Results Good hand washing practice at critical times was reported in 52.2% (95% CI: 47.5, 57.2%) of study participants. Desirable attitude [AOR = 3.37, 95% CI (2.03, 5.58)], presence of water for washing hands [AOR = 4.86, 95% CI (1.26, 18.69)] and a good knowledge [AOR = 2.98, 95% CI (1.92, 4.60)] were significantly associated factors with hand washing practice at critical times. Conclusion The hand washing practice at critical times of study participants was found to be low. A significant proportion of mothers of under five children have a poor hand washing practice at critical times. It is necessary to increase the access to water and to improve knowledge and attitude of mothers to improve their hand washing practice at critical times.

NUTRITIONAL STATUS OF UNDER-FIVE CHILDREN IN BANGLADESH: A MULTILEVEL ANALYSIS

2012 ◽  
Vol 44 (5) ◽  
pp. 525-535 ◽  
Author(s):  
JAHANGIR ALOM ◽  
MD. ABDUL QUDDUS ◽  
MOHAMMAD AMIRUL ISLAM
Keyword(s):  
Nutritional Status ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Contributing Factors ◽  
Related Factors ◽  
Logistic Regression Models ◽  
Under Five ◽  
Under Five Children ◽  
Random Intercept ◽  
Health Related

SummaryThe nutritional status of under-five children is a sensitive sign of a country's health status as well as economic condition. This study investigated the differential impact of some demographic, socioeconomic, environmental and health-related factors on the nutritional status among under-five children in Bangladesh using Bangladesh Demographic and Health Survey 2007 data. Two-level random intercept binary logistic regression models were used to identify the determinants of under-five malnutrition. The analyses revealed that 16% of the children were severely stunted and 25% were moderately stunted. Among the children under five years of age 3% were severely wasted and 14% were moderately wasted. Furthermore, 11% of the children were severely underweight and 28% were moderately underweight. The main contributing factors for under-five malnutrition were found to be child's age, mother's education, father's education, father's occupation, family wealth index, currently breast-feeding, place of delivery and division. Significant community-level variations were found in the analyses.

scholarly journals Socio-Economic Correlates of Children's Nutritional Status: Evidence from Pakistan Demographic and Health Survey 2017-18

2020 ◽  
Vol V (I) ◽  
pp. 221-233
Author(s):  
Muhammad Shahid ◽  
Inam Ullah Leghari ◽  
Farooq Ahmed
Keyword(s):  
Logistic Regression ◽  
Nutritional Status ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Composite Index ◽  
Binary Logistic Regression ◽  
Household Wealth ◽  
Nutrition Status ◽  
Binary Logistic Regression Model ◽  
Important Indicator

Nutrition status is an important indicator of child health. This study estimates the effect of socioeconomic determinants on children's nutritional status of under five years of age. We apply the Composite Index of Anthropometric Failure (CIAF) in our empirical analysis as a proxy measure to denote the malnutrition measurement index, and a binary logistic regression model using PDHS dataset for 2017-18. The logistic regression model inspects the probability of malnutrition among children. The result demonstrates that the age of children, education and employment status of mothers, BMI of mothers, assets owned by mothers, tetanus vaccination of mothers, the incidence of diarrhea in children, and household wealth has a significant impact on malnutrition in children. The study concludes that socioeconomic deprivations and inequalities in society play a significant role in determining the health and nutrition of pre-school children.

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