Specification and Estimation of a Biometric Model by Using Logistic Regression for Measuring Child Mortality

SummaryCensus data were used to investigate the influences of socioeconomic and environmental variables on child mortality rates in southern Brazil. By multivariate logistic regression analysis the effects of correlated factors were distinguished, after adjustment for maternal age and parity. Low family income and, to a lesser degree, low employment status of the head of the family were associated with high child mortality levels. Place of residence, education of the mother and of the head of the family, availability of piped water in the home, access to a toilet and type of housing were all associated with childhood mortality variation, even after allowing for the effects of income and employment. The contributions of the source of the water supply and type of sanitation facilities, however, were less clear and tended to become unimportant after controlling for the socioeconomic variables. There was also no apparent advantage in being covered by government health insurance.

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Factors determining child mortality in Uganda

International Journal of Social Economics ◽

10.1108/ijse-08-2015-0201 ◽

2017 ◽

Vol 44 (5) ◽

pp. 633-642 ◽

Cited By ~ 3

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.

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Pediatric Burn Outcome; Diagnostic Value of R-Baux and P-Baux Scores

10.21203/rs.3.rs-45955/v1 ◽

2020 ◽

Author(s):

Kavous Shahsavari Nia ◽

Alireza Razzaghi ◽

Farzad Rahmani ◽

Hassan Soleimanpour ◽

Ayda Khalili ◽

...

Keyword(s):

Logistic Regression ◽

Child Mortality ◽

Mortality Risk ◽

Diagnostic Value ◽

Study Data ◽

Health Providers ◽

Significant Relation ◽

Cross Sectional ◽

Common Causes ◽

Northwest Of Iran

Abstract Objective: The purpose of this study was to determine the value of R-Baux and P-Baux indexes in predicting the pediatric burn outcome. Using prospective cross-sectional method, 213 children under 12 years old admitted with burn in burn referral hospital in Northwest of Iran were included in the study. Data were collected using goal-driven questionnaire including patients' demographics and burn clinical data and outcome. Results: About 59.6% of participants were male. The most common causes of burns was burning with boiling water (127; 69%). For outcome of death, the AUC for the scores of P.Baux and R.Baux were same with 0.959. The AUC for death were 982% and 992% for P.Baux and R.Baux respectively. Also, for the outcome of admission to ICU the AUC were same with 959%. A significant relation between R-Baux and P-Baux scores with patients need for intubation was determined based on logistic regression (p=0.01). Conclusions: The R-Baux and P-Baux scores were related to the probability of intubation, ICU admission and mortality. Using these scores not only predicts mortality risk, but also provide the opportunity for health providers to prioritize patients and provide proper facilities and services to prevent child mortality due to burn.

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SIBLING MORTALITY CORRELATION IN KENYA

Journal of Biosocial Science ◽

10.1017/s0021932000002650 ◽

2000 ◽

Vol 32 (2) ◽

pp. 265-278 ◽

Cited By ~ 3

Author(s):

LAWRENCE IKAMARI

Keyword(s):

Logistic Regression ◽

Data Analysis ◽

Infant Mortality ◽

Empirical Evidence ◽

Child Mortality ◽

Mortality Rates ◽

Control Variables ◽

Mortality Risks ◽

Survival Status ◽

Infant And Child Mortality

This paper examines whether infant and child mortality risks among successive siblings are closely correlated, and if so, whether the survival status of the preceding child is an important factor affecting infant and child mortality in Kenya. The data were drawn from the 1988/89 Kenya Demographic and Health Survey. Logistic regression was used as the major method of data analysis. The results show that both infant and child mortality rates are significantly higher among subsequent children whose preceding siblings had died in infancy than for those whose preceding sibling had survived through infancy. The effect of the survival status of the preceding child on infant mortality was statistically strong, even after a large number of control variables were taken into account. However, its effect on child mortality appears to be spurious since it was rendered statistically insignificant when just a few control variables were introduced into the analysis. The results provide empirical evidence that infant and child mortality risks among successive siblings are closely correlated in Kenyan families, and that the effect of the survival status of the preceding child is important in determining infant mortality but not child mortality.

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Individual, Household and Community-Level Effects of Infant and Child Mortality in Nigeria: A Logistic Regression Approach

Global Journal of Health Science ◽

10.5539/gjhs.v10n10p136 ◽

2018 ◽

Vol 10 (10) ◽

pp. 136

Author(s):

Simeon Olawuwo ◽

N. Forcheh ◽

S. Setlhare

Keyword(s):

Logistic Regression ◽

Child Mortality ◽

Child Survival ◽

Significant Risk ◽

Childhood Mortality ◽

Individual Level ◽

Geographical Variations ◽

Infant And Child Mortality ◽

Individual Household ◽

The Individual

Research has shown that knowledge about the determinants of childhood mortality at the individual level is not enough to address the problem because the characteristics of the environment where a child is born tend to alter individual level characteristics and thereby affect child survival. The study used data from the 2013 Nigeria Demographic and Health Survey (NDHS). The fact that a child was either dead or alive was assumed to be accurately recorded. Hence, logistic regression model was used to model whether a child is dead or alive with respect to the selected predictor variables. Results from the study reveal that infant and child mortality in Nigeria is determined more by individual household than by community, and that geographical variations also exist. This study has identified significant risk factors that will help policy makers to formulate policies that will improve childhood survival.

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How Useful is the Power Law of Practice for Recognizing Practice in Concentration Tests?

European Journal of Psychological Assessment ◽

10.1027/1015-5759.23.3.157 ◽

2007 ◽

Vol 23 (3) ◽

pp. 157-165 ◽

Cited By ~ 4

Author(s):

Carmen Hagemeister

Keyword(s):

Logistic Regression ◽

Reaction Time ◽

Power Law ◽

Error Rate ◽

Reaction Times ◽

Practice Effect ◽

Practice Effects ◽

Rate Decrease ◽

Small Practice

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.

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Perceived Effectiveness of Random Testing for Alcohol and Drugs in the Australian Aviation Community

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000031 ◽

2012 ◽

Vol 2 (2) ◽

pp. 72-81

Author(s):

Christina M. Rudin-Brown ◽

Eve Mitsopoulos-Rubens ◽

Michael G. Lenné

Keyword(s):

Logistic Regression ◽

Online Survey ◽

Random Testing ◽

Regression Analyses ◽

Perceived Effectiveness ◽

Student Pilots ◽

Alcohol And Drugs ◽

Positive Attitudes ◽

One Year ◽

Alcohol And Other Drugs

Random testing for alcohol and other drugs (AODs) in individuals who perform safety-sensitive activities as part of their aviation role was introduced in Australia in April 2009. One year later, an online survey (N = 2,226) was conducted to investigate attitudes, behaviors, and knowledge regarding random testing and to gauge perceptions regarding its effectiveness. Private, recreational, and student pilots were less likely than industry personnel to report being aware of the requirement (86.5% versus 97.1%), to have undergone testing (76.5% versus 96.1%), and to know of others who had undergone testing (39.9% versus 84.3%), and they had more positive attitudes toward random testing than industry personnel. However, logistic regression analyses indicated that random testing is more effective at deterring AOD use among industry personnel.

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