scholarly journals Two Level Logistic Regression Model of Factors Influencing in Early Childbearing and its Consequences on Nutritional Status of Bangladeshi Mothers: Nationally Representative Data

2021 ◽  
Vol 10 ◽  
pp. 97-106
Author(s):  
Khirujjaman Sumon ◽  
Md. Abu Sayem ◽  
Abu Sayed Md. Al Mamun ◽  
Premananda Bharati ◽  
Suman Chakrabarty ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Nutritional Status ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Household Wealth ◽  
Medical Problem ◽  
Early Marriage ◽  
Early Childbearing ◽  
Modifiable Factors ◽  
Study Results

Background: Early marriage and early pregnancy is a social as well as a medical problem in developing countries, which may have an impact on the health and nutritional status of teenage mothers. Therefore, the objective of this study was to determine the influencing factors of early childbearing (ECB) and its consequences on the nutritional status of Bangladeshi mothers. Methods: Data was extracted from Bangladesh Demographic and Health Survey (BDHS-2014). Women who delivered their first baby before the age of 20 years are considered ECB mothers. Nutritional status was measured by body mass index (BMI). Chi-square test and both univariable and multivariable logistic regressions, and z-proportional test were used in this study. Results: The prevalence of ECB among currently non-pregnant mothers in Bangladesh was 83%. The logistic regression model provided the following six risk factors of ECB: (i) living location (division) (p<0.01), (ii) respondents’ education (p<0.05), (iii) husbands’ education (p<0.05), (iv) household wealth quintiles (p<0.01), (v) respondents’ age at first marriage (p<0.05), and (vi) number of family members (p<0.05). Still, 17.6% of mothers were undernourished in Bangladesh; among them, 18.5% and 13.4% were ECB and non- ECB mothers respectively. ECB mothers had a greater risk to be undernourished than non-ECB mothers [COR=1.26, 95% CI: 1.11-1.43; p<0.01]. Conclusions: In this study, some modifiable factors were found as predictors of ECB in Bangladesh. ECB mothers were more prone to become under-nourished. These findings can be considered to reduce the number of ECB mothers in Bangladesh consequently improve their nutritional status.

scholarly journals Factors Influencing in Early Childbearing and Its Consequences on Nutritional Status of Bangladeshi Mothers: Nationally Representative Data

2020 ◽  
Author(s):  
Khirujjaman Sumon ◽  
Md. Abu Sayem ◽  
Abu Sayed Md Al Ma ◽  
Premananda Bharati ◽  
Suman Chakrabarty ◽  
...  
Keyword(s):  
Nutritional Status ◽  
Binary Logistic Regression ◽  
Household Wealth ◽  
Medical Problem ◽  
Early Marriage ◽  
Binary Logistic Regression Model ◽  
Early Childbearing ◽  
Chi Square ◽  
Modifiable Factors ◽  
Nationally Representative

Abstract Background: Early marriage and early pregnancy is a social as well as medical problem in developing countries, which may have an impact on health and nutritional status of teenage mothers. Therefore, the objective of this study was to determine the influencing factors of early childbearing (ECB) and its consequences on nutritional status of Bangladeshi mothers. Methods: Data was extracted from the last survey of Bangladesh Demographic and Health Survey (BDHS-2014). Women who delivered their first baby before their age 20 years are considered as ECB mothers. Nutritional status was measured by body mass index (BMI) which was categorized as (i) under nutrition (BMI<18.5 kg/m2), (ii) normal (18.5≤BMI<25 kg/m2) and (iii) over nutrition BMI≥25 kg/m2). Chi-square test and both univariable and multivariable logistic regressions, and z-proportional test were used in this study. Results: This study revealed that the prevalence of ECB among currently non-pregnant mothers in Bangladesh was 83% (urban: 77% and rural: 85.8%). A multivariable binary logistic regression model provided the following six risk factors of ECB: (i) living location (division), (ii) respondents’ education, (iii) husbands’ education, (iv) household wealth quintiles, (v) respondents’ age at first marriage, and (vi) number of family members. Still 17.6% mothers were undernourished in Bangladesh; among them 18.5% and 13.4% were ECB and non- ECB mothers respectively, while 25.5% mothers were over nourished. Univariable model demonstrated that ECB mothers had a greater risk to be undernourished than non-ECB mothers [COR=1.26, 95% CI: 1.11-1.43; p<0.01]. Conclusions: In this study, some modifiable factors were found as predictors of ECB in Bangladesh. ECB mothers were more prone to become under-nourished. These findings can be considered to reduce the number of ECB mothers in Bangladesh consequently to improve their nutritional status.

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.

Factors determining child mortality in Uganda

2017 ◽  
Vol 44 (5) ◽  
pp. 633-642 ◽  
Author(s):  
Will Kaberuka ◽  
Alex Mugarura ◽  
Javan Tindyebwa ◽  
Debra S. Bishop
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Birth Weight ◽  
Regression Model ◽  
Marital Status ◽  
Birth Order ◽  
Child Mortality ◽  
Logistic Regression Model ◽  
Household Wealth ◽  
Content Type

Purpose The purpose of this paper is to establish socio-economic factors and maternal practices that determine child mortality in Uganda. Design/methodology/approach The paper examines the role of sex, birth weight, birth order and duration of breastfeeding of a child; age, marital status and education of the mother; and household wealth in determining child mortality. The study employs a logistic regression model to establish which of the factors significantly impacts child mortality in Uganda. Findings The study established that education level, age and marital status of the mother as well as household wealth significantly impact child mortality. Also important are the sex, birth weight, birth order and breastfeeding duration. Research limitations/implications Policies aimed at promoting breastfeeding and education of female children can make a significant contribution to the reduction of child mortality in Uganda. Practical implications Health care intervention programs should focus on single, poor and uneducated mothers as their children are at great risk due to poor and inadequate health care utilization. Originality/value This paper could be the first effort in examining child mortality status in Uganda using a logistic regression model.

scholarly journals Binary Logistic Regression Model for Assessing Factors Associated with Nutritional Status of Children Under Five Years among Chepang Community in Siddi, Chitwan, Nepal

2020 ◽  
Vol 4 ◽  
pp. 43-56
Author(s):  
Ravi Kiran Poudel ◽  
Shankar Prasad Khanal
Keyword(s):  
Logistic Regression ◽  
Nutritional Status ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Family Income ◽  
Children Under Five ◽  
Under Five ◽  
Factors Associated ◽  
Number Of Children ◽  
Nutritional Status Of Children

Background: Chepang Community in Nepal has often been characterized as the poorest among Nepal’s poor, and has faced food insecurity at a household level each year. Health status of their children is poor compared to other community children and more so for the age group under the age of five years. Objective: To find the proportion of stunting, wasting and underweight, and to assess the most promising factors associated with the nutritional status of children under five years of Chepang community in Siddi, Chitwan, Nepal. Materials and Methods: A cross-sectional research design was used with 170 samples. To find the association of different factors with the nutritional status of children under 5 years of age (stunting, wasting and underweight, each) binary multiple logistic regression model was used and the goodness of fit of the model was assessed through Hosmer and Lemeshow test. Results: The overall proportion of children under five years of the Chepang community is 60.6%, 30.6% and 44.7% for underweight, stunting and wasting respectively. Among many factors, the mother’s illiteracy (OR: 5.30, 95 % CI: 1.37 to 21.57), external monthly family income (≤ NRs. 2000) (OR: 9.65, 95 % CI: 3.23 to 30.78) and food availability for six months from own land (OR: 4.17, 95 % CI: 1.90 to 17.98) have a significant association with underweight. Similarly, for stunting, female child (OR: 2.19, 95 % CI: 1.02 to 4.70), number of children (more than one) below 14 years at home (OR: 4.15, 95 % CI : 1.77 to 11.04) and external family income (≤ NRs. 2000) (OR: 4.42, 95% CI: 1.01 to 17.06) are significantly associated, and for wasting, a number of children (more than one) below 14 years at home (OR: 4.64, 95 % of CI: 1.71 to 12.60) and external family income (≤ NRs. 2000) (OR: 5.17, 95 % CI: 2.27 to 11.79) are significantly associated. Conclusion: Substantial numbers of children from Chepang community are having the problem of underweight, stunting and wasting. Different demographic and socio-economic variables have been found associated for odds of having low level of nutritional status of children.

Study on Early Warning of Enterprise Financial Distress — Based on Partial Least-squares Logistic Regression

2015 ◽  
Vol 65 (s2) ◽  
pp. 3-16 ◽  
Author(s):  
Kun Xu ◽  
Qilan Zhao ◽  
Xinzhong Bao
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Least Squares ◽  
Partial Least Squares ◽  
Early Warning ◽  
Financial Distress ◽  
Logistic Model ◽  
Logistic Regression Model ◽  
Warning System ◽  
Study Results

Establishment of an effective early warning system can make the company operators make relevant decisions as soon as possible when finding the crisis, improve the operating results and financial condition of enterprise, and can also make investors avoid or reduce investment losses. This paper applies the partial least-squares logistic regression model for the analysis on early warning of enterprise financial distress in consideration of quite sensitive characteristics of common logistic model for the multicollinearity. The data of real estate industry listed companies in China are used to compare and analyze the early warning of financial distress by using the logistic model and the partial least-squares logistic model, respectively. The study results show that compared with the common logistic regression model, the applicability of partial least-squares logistic model is stronger due to its eliminating multicollinearity problem among various early warning indicators.

Does micronutrients intake modulate the risk of coronary heart disease?

2019 ◽  
Vol 49 (3) ◽  
pp. 368-380 ◽  
Author(s):  
Mohammed Azab ◽  
Abdel-Ellah Al-Shudifat ◽  
Lana Agraib ◽  
Sabika Allehdan ◽  
Reema Tayyem
Keyword(s):  
Coronary Heart Disease ◽  
Logistic Regression ◽  
Heart Disease ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Daily Intake ◽  
Dietary Intakes ◽  
Content Type ◽  
Study Results

Purpose The purpose of this study was to examine the relationship between micronutrient intake and coronary heart disease (CHD) in middle-aged Jordanian participants. Design/methodology/approach A case-control study was conducted among patients referring for elective coronary angiography. A total of 400 patients were enrolled in this study. Face-to-face interview was used to complete food frequency questionnaire from which the authors derived usual daily intake of micronutrients. The mean age of participates was 52 years and their average BMI was 30.7 kg/m2. Multinomial logistic regression model and linear logistic regression model were used to calculate odd ratios (OR) and its 95 per cent confidence interval (CI) and p-value for trend, respectively. The association between the risk of CHD and micronutrients intake was adjusted for the age, gender, BMI, smoking, physical activity, total energy intake, occupation, education level, marital status and family history. Findings The study results showed no significant differences between cases and controls for dietary intakes of micronutrients, except for the intake of calcium (p < 0.005), magnesium (p < 0.025), phosphorus (p < 0.023) and potassium (p < 0.006) which were lower in cases than controls. Although no significant trend was observed between most of the dietary intake of micronutrients and the risk of developing CHD, a significant protective effect of magnesium [OR 0.52; 95 per cent CI (0.29-0.95)], phosphorus [OR 0.44; 95 per cent CI (0.24-0.80)] and potassium [OR 0.41; 95 per cent CI (0.22-0.74)] against the risk of CHD was detected. Originality/value The findings from this study provide strong evidence that the intake of micronutrients such as calcium, magnesium, phosphorus and potassium has no significant associations with the risk of CHD.

Identification of Secondary Crash Risk Factors using Penalized Logistic Regression Model

2019 ◽  
Vol 2673 (11) ◽  
pp. 901-914 ◽  
Author(s):  
Angela E. Kitali ◽  
Priyanka Alluri ◽  
Thobias Sando ◽  
Wensong Wu
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Real Time ◽  
Logistic Regression Model ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Mitigation Strategies ◽  
Study Results ◽  
Highly Correlated ◽  
Penalized Logistic Regression

Secondary crashes (SCs) have increasingly been recognized as a major problem leading to reduced capacity and additional traffic delays. However, the limited knowledge on the nature and characteristics of SCs has largely impeded their mitigation strategies. There are two main issues with analyzing SCs. First, relevant variables are unknown, but, at the same time, most of the variables considered in the models are highly correlated. Second, only a small proportion of incidents results in SCs, making it an imbalanced classification problem. This study developed a reliable SC risk prediction model using the Least Absolute Shrinkage and Selection Operator (LASSO) penalized logistic regression model with Synthetic Minority Oversampling TEchnique-Nominal Continuous (SMOTE-NC). The proposed model is considered to improve the predictive accuracy of the SC risk model because it accounts for the asymmetric nature of SCs, performs variable selection, and removes highly correlated variables. The study data were collected on a 35-mi I-95 section for 3 years in Jacksonville, Florida. SCs were identified based on real-time speed data. The results indicated that real-time traffic variables and primary incident characteristics significantly affect the likelihood of SCs. The most influential variables included mean of detector occupancy, coefficient of variation of equivalent hourly volume, mean of speed, primary incident type, percentage of lanes closed, incident occurrence time, shoulder blocked, number of responding agencies, incident impact duration, incident clearance duration, and roadway alignment. The study results can be used by agencies to develop SC mitigation strategies, and therefore improve the operational and safety performance of freeways.

Truck Driver Turnover

2018 ◽  
pp. 382-404 ◽  
Author(s):  
S. Scott Nadler ◽  
John F. Kros
Keyword(s):  
Social Psychology ◽  
Logistic Regression ◽  
Regression Model ◽  
Theoretical Approach ◽  
Logistic Regression Model ◽  
Reasoned Action ◽  
The Social ◽  
Study Results ◽  
Psychology Literature ◽  
Managerial Perspective

The purpose of this chapter is to identify those constructs that lead to driver turnover and to develop a logistic regression model to assist in predicting driver turnover. Interviews with drivers were conducted with 154 drivers at large truck stops. The theory of reasoned action (TRA), originating in the social psychology literature, is the theoretical approach in this study. This chapter makes contributions in two areas. From a managerial perspective, the study results indicate that companies can use a technique such as logistic regression as part of their driver-retention efforts in order to create competitive advantage by increasing efficiency and cutting costs. The resulting logistic regression model provides a concrete tool for analyzing driver turnover. Based on four factors, the model accounts for 84% of the variance and accurately predicts which drivers or driver classes are most at risk of turning over.

PROFILE OF THE HEALTH AND NUTRITIONAL STATUS OF OLDER ADULTS IN MEXICO. 2012 NATIONAL HEALTH AND NUTRITION SURVEY

2013 ◽  
pp. 1-8
Author(s):  
T. SHAMAH LEVY ◽  
L. CUEVAS NASU ◽  
M.C. MORALES RUAN ◽  
V. MUNDO ROSAS ◽  
I. MENDEZ GOMEZ-HUMARAN ◽  
...  
Keyword(s):  
Older Adults ◽  
Logistic Regression ◽  
Nutritional Status ◽  
Regression Model ◽  
National Health ◽  
Logistic Regression Model ◽  
Healthy Adult ◽  
Nutrition Survey ◽  
Health And Nutrition ◽  
Adult Status

Background:The health and nutritional conditions of older adults in Mexico are heterogeneous. Theprevalence of chronic noncommunicable diseases is elevated with disparities in functionality and socioeconomicinequities. Objectives:To obtain updated information of the health and nutritional profile of older adults inMexico in a national representative sample. Methods:Information was obtained from 6,687 60 years and olderadults from the 2012 National Health and Nutrition Survey (ENSANUT 2012). An index defining the status of"healthy adult" was constructed taking into account the variables of independence in performing activities ofdaily living (ADL), based on the development by Katz, instrumental ADL, no chronic diseases, nonsmoker andno active use of alcohol. Tables of frequencies and proportions were constructed and expanded to describe thegeneral characteristics and nutritional status of the adult Mexican population. A logistic regression model wasused to study changes in the probability of being classified as a healthy adult with respect to different variables ofinterest. Probabilities using the delta method were estimated to establish 95% confidence intervals. Results:Inthis study 12.2% of the older adults, were classified as healthy. The logistic regression model adjusted for thevariables included in the study shows that the interaction of age and gender is significant (P = 0.068), where theprobability of healthy adult status decreases in women with ageing and remains stable for men. Also, living in thesouthern region of the country significantly decreases the probability of healthy adult status (P = 0.001). Genderof the older adult was not significant. Conclusions:In Mexico, the health conditions of older adults are deficient.Public policies need to be generated that are directed at this population group and will translate into self-careactions in the early stages of life so as to guarantee a healthy future.

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