PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF BIVARIAT DENGAN MODEL GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL BIVARIAT REGRESSION (GWNBBR) PADA KASUS ANGKA KEMATIAN BAYI DAN KEMATIAN IBU DI JAWA TENGAH

Infant mortality (0-11 months) and maternal mortality (during pregnancy, childbirth, and postpartum) are significant indicators in determining the level of public health. Central Java Province which has 35 regencies/cities is included in the top five regions with the highest number of infant and maternal mortality in Indonesia. The data characteristics of the number of infants and maternal mortality are count data. Therefore, the Poisson Regression method can be used to analyze the factors that influence the number of infants and maternal mortality. In Poisson regression analysis, there must be a fulfilled assumption, called equidispersion. Frequently, the variance of count data is greater than the mean, which is known as the overdispersion. The research, binomial negative bivariate regression is used as a solutions to overcome the problem of overdispersion in poisson regression. This method produce a global model. In reality, the geographical, socio-cultural, and economic conditions of each region will be different. This illustrates the effect of spatial heterogeneity, so it needs to be developed into Geographically Weighted Negative Binomial Bivariate Regression (GWNBBR). The model of GWNBBR provides weighting based on the position or distance from one observation area to another. Significant variables for modeling infant mortality cases included the percentage of obstetric complications treated (X1), the percentage of infants who were exclusively breastfed (X3), and the percentage of poor people (X5). Significant variable for modeling maternal mortality cases is the percentage of poor people (X5). Based on the AIC value, GWNBBR model is better than binomial negatif bivariat regression model because it has a smaller AIC value.

Structural Racism is Associated with Assisted Living Location

Our objective was to measure the association between structural racism, a previously unmeasured but theoretically causal factor, and assisted living communities (ALCs) location as fewer ALCs are located in counties with a greater percentage of the population reported as Black (PPB). We used a recently developed measure of structural racism—the racial opportunity gap (ROG), which compares the economic mobility of Black and White people who grew up in the same area with parents who had similar incomes. We estimated a multilevel mixed-effects bivariate regression model to examine the factors contributing to the presence of ALC. We relied on state and county random effects. The likelihood of an assisted living being located in a census tract in 2019 was significantly positively associated with the percent of the population over the age of 65 (OR=150.1573, p=<0.001), the PPB (OR=2.9916, p=0.004), and higher median incomes (OR=1.0, p=<0.001). In contrast, rurality (OR=0.5656, p=<0.001), unemployment rates (OR=0.0288, p=<0.001), and census tracts that have a high PPB in addition to a high county ROG (OR=.0058, p=0.0137) are all associated with a lesser likelihood of an ALC. The interaction coefficient between the ROG and PPB reverses the previously documented negative association between the PPB and ALC presence. This result empirically supports the premise that structural racism, not population race alone, is a negative determinant of where an ALC is located within a county.

Unfolding the Linkage Between SCM Practices and Customer Responsiveness in Indian Automotive and Aerospace Manufacturing Firms

The study examines how the supply chain management (SCM) practices impact customer responsiveness, and the same has been tested empirically with the help of a conceptual framework based on a literature review. Previous studies on the relationship between supply chain variables and competitive advantage have been presented earlier with variables including customer satisfaction, quality and flexibility. Still, there is a shortage of literature on customer responsiveness. This study attempts to conduct a structured study well supported by the existing literature to establish the mentioned linkage. The study sample includes 433 employees from 10 Indian automobile and aerospace manufacturing organizations, and the responses have been analysed with structural equation modelling (SEM) and bivariate regression. The study establishes the linkage between SCM practices and customer responsiveness. The results infer that supply chain practices are antecedents to customer responsiveness. The study has also scrutinized the specific items of SCM practices construct that highly influences customer responsiveness. This study also highlights and identifies the research on the linkage between SCM practices and customer responsiveness in the Indian context. For practitioners, this study offers advice for effective policymaking to have more excellent customer responsiveness by concentrating on the specific elements of each SCM practice.

HOTEL INDUSTRY COMPETITIVENESS IN COVID 19 PANDEMIC ENVIRONMENT IN KENYA: HOW TECHNOLOGICALLY READY ARE THE HOTELS?

Since December 2019, the COVID-19 pandemic has had a devastating impact on te totel industry leading to deep losses among industry players and forcing some to shut down altogether. For those that would survive the crisis, their competitiveness could be at risk unless they demonstrate strategic readiness. The competitiveness found in modern organizations is, however, increasingly determined by the strategic readiness or capability of it assets, notably technology. However, the strategic readiness of the hotel industry needed to be established. Therefore, this paper explores the strategic teachnology readiness of the star-rated hotels in Kenya for competitiveness in the Covid 19 pandemic environment. The paper is guided by the Chamberlain's theory of strategy. A descriptive cross sectional survey design targeting 138 star-rated hotels in the country selected through systematic random sampling. Data was collected using questionnaires and interview schedules. Qualitative data was analyzed using content anaysis with the aid of Nvivo software while quantitative data was analyzed using both ddescriptive and inferential statistical analysis with the aid of SPSS version 24.0. Specifically, the study used the bivariate regression model to assess the relationship between the variables. The study found that technology readiness significantly influenced the competitiveness of star-rated hotels in the Covid 19 pandemic environment in Kenya. There is need for the hotels to adopt a more proacticve approach in setting their technological systems for any eventualities as this will be less expensive and enable their users to be more acquainted with the systems in advance. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0892/a.php" alt="Hit counter" /></p>

The ABC of linear regression analysis: What every author and editor should know

Regression analysis is a widely used statistical technique to build a model from a set of data on two or more variables. Linear regression is based on linear correlation, and assumes that change in one variable is accompanied by a proportional change in another variable. Simple linear regression, or bivariate regression, is used for predicting the value of one variable from another variable (predictor); however, multiple linear regression, which enables us to analyse more than one predictor or variable, is more commonly used. This paper explains both simple and multiple linear regressions illustrated with an example of analysis and also discusses some common errors in presenting the results of regression, including inappropriate titles, causal language, inappropriate conclusions, and misinterpretation.

What are the biopsychosocial risk factors associated with pain in postpartum runners? Development of a clinical decision tool

Background In 2019, a majority of runners participating in running events were female and 49% were of childbearing age. Studies have reported that women are initiating or returning to running after childbirth with up to 35% reporting pain. There are no studies exploring running-related pain or risk factors for this pain after childbirth in runners. Postpartum runners have a variety of biomechanical, musculoskeletal, and physiologic impairments from which to recover from when returning to high impact sports like running, which could influence initiating or returning to running. Therefore, the purpose of this study was to identify risk factors associated with running-related pain in postpartum runners with and without pain. This study also aimed to understand the compounding effects of multiple associative risk factors by developing a clinical decision tool to identify postpartum runners at higher risk for pain. Methods Postpartum runners with at least one child ≤36 months who ran once a week and postpartum runners unable to run because of pain, but identified as runners, were surveyed. Running variables (mileage, time to first postpartum run), postpartum variables (delivery type, breastfeeding, incontinence, sleep, fatigue, depression), and demographic information were collected. Risk factors for running-related pain were analyzed in bivariate regression models. Variables meeting criteria (P<0.15) were entered into a multivariate logistic regression model to create a clinical decision tool. The tool identified compounding factors that increased the probability of having running-related pain after childbirth. Results Analyses included 538 postpartum runners; 176 (32.7%) reporting running-related pain. Eleven variables were included in the multivariate model with six retained in the clinical decision tool: runner type-novice (OR 3.51; 95% CI 1.65, 7.48), postpartum accumulated fatigue score of >19 (OR 2.48; 95% CI 1.44, 4.28), previous running injury (OR 1.95; 95% CI 1.31, 2.91), vaginal delivery (OR 1.63; 95% CI 1.06, 2.50), incontinence (OR 1.95; 95% CI 1.31, 2.84) and <6.8 hours of sleep on average per night (OR 1.89; 95% CI 1.28, 2.78). Having ≥ 4 risk factors increased the probability of having running-related pain to 61.2%. Conclusion The results of this study provide a deeper understanding of the risk factors for running-related pain in postpartum runners. With this information, clinicians can monitor and educate postpartum runners initiating or returning to running. Education could include details of risk factors, combinations of factors for pain and strategies to mitigate risks. Coaches can adapt running workload accounting for fatigue and sleep fluctuations to optimize recovery and performance. Future longitudinal studies that follow asymptomatic postpartum women returning to running after childbirth over time should be performed to validate these findings.

Effectors of income-child health gradient: Role of dietary diversity on child nutritional status in selected slums of Dhaka city

Child dietary diversity (CDD) is an important nutritional outcome measuring the economic ability of a household to access a variety of foods during a determined period. Relating household income to CDD and child anthropometric failure, a cross-sectional study was conducted among 275 selected Dhaka city slum children of 6-12 years. Prevalence of stunting (18%), wasting (19.4%), and underweight (22%) among them were found similar to the current national figure. However, a sizable number of households showed increased DDS (>5), thereby indicating an increased household purchasing power (PP). Bivariate regression analysis showed that children from lower family income (≤6000 BDT) were 3 times more likely to be stunted as compared to children with greater family income [Unadjusted OR=3.097, 95% CI (1.578-6.077), p=0.001]. Furthermore, logistic regression showed that children who had <5 DDS were 2 times more likely to be stunted than children who had ≥5 DDS [Adjusted OR=2.127, 95% CI (1.051- 4.305), p=0.036]. Therefore, an inverse association has been found between CDD and their anthropometric failure. J. Bangladesh Acad. Sci. 45(1); 85-94: June 2021

Impact of Coronavirus Pandemic on Financial Market Stability in Africa

The outbreak of the coronavirus in December 2019, with its accompanying declaration as a pandemic by the World Health Organisation in March 2020, resulted in lockdown of the global financial markets. This paper uses data from pre-coronavirus, coronavirus endemic and coronavirus pandemic periods to evaluate the impact of coronavirus pandemic on stability of Africa stock markets, sovereign bond markets and U.S. dollar exchange rates in Kenya, Morocco, Nigeria and South Africa as well as Africa Sharia equity and Sukuk indices. Findings from study suggest that Africa financial markets became very unstable during the coronavirus pandemic than during the endemic and pre-coronavirus periods. Results from bivariate regression model show evidence of negative impact of coronavirus pandemic on financial market returns. The results further show that Africa financial markets return volatility increases as the number of coronavirus cases increases. Overall, the findings suggest that coronavirus has negative impact on financial markets’ returns and exacerbated financial markets instability thus retarding sustainable economic development in the continent.

Outcomes of Bacterial Meningitis Treatment and its Associated Risk Factors among the Children of Nawabshah, Pakistan

Background: Meningitis happens all the more ordinarily during the main month of life than during some other ensuing period and it is related with high horribleness and mortality. Objective: The objective of this study is to assess the outcomes of meningitis treatment and its associated risk factors among the children. Methodology: A cross-sectional retrospective study was conducted on 400 children, sample size was calculated by using Slovin’s Formula “n=N÷(1+Ne2)” at 0.05 margin of error and by using convenience sampling. Patients who were diagnosed with bacterial meningitis aged from 0 to 18 years were included in the study. Data was collected by well-structured questionnaire. SPSS version 23.0 was used to analyze the data. Multivariate logistic and Bivariate regression analyses was performed to analyze the data. P value ≤0.05 was considered as statistical significant. Results: 262 (65.5%) males were reported and females were 138 (34.5%). Sepsis was found in 24 (6%) patients due to meningitis. Outcomes of the treatment of meningitis patients were found good among 308 (77%) patients. Conclusion: It was concluded that adjustments of starting anti-toxin routine, level of obviousness at hospitalization and season of show to the medical care office from indication beginning altogether affected therapy results of intense bacterial meningitis in youngsters.

HISTOMORPHOMETRIC ESTIMATION OF AGE FROM BONE SAMPLES OF NIGERIANS

Background. Age estimation is crucial in creating the biological profile of unknown skeletal remains and recently there is emphasis on the need to develop population specific forensic baseline data for easy identification of these remains. Objective. The aim of this study is to estimate age from the histomorphometric features of the bones of Nigerians. Methods. Fragments of non-pathologic bone samples were collected during orthopaedic procedures. Ground sections were prepared using Modified Frost’s manual method of bone preparation to determine the following histologic parameters; haversian canal diameter (HCD), primary and secondary osteons, number of osteon fragments and non-haversian canal as well as haversian canal area (HCA). 29 subjects aged 35 to 85 years old were used for the study. Bone fragments included samples from the femur, tibia, humerus, and the vertebrae. Data obtained were subjected to descriptive statistics, Pearson’s correlation, bivariate regression equation, Student t-test and analysis of variance (ANOVA). Results. The mean age for our population was 58.86 years old. ANOVA showed significant variation in the average HCD for the various regions: humerus=8.45±2.48, femur=7.09±4.06, tibia=8.70±2.52 and verte­brae=3.69±0.73. There was a strong inverse relationship between age and primary osteons. The total number of osteon fragments increased with age while total number of primary osteons and average HCD decreased with age. The HCA, though statistically insignificant, also decreased with age. Conclusion. Our findings show that three histomorphometric parameters showed significant correlation with age: osteon fragments (OS-f), primary osteons (OS-p) and HCD. The histomorphometric parameters were therefore relevant in age estimation. Objective: The aim of this study is to estimate age from the histologic features of the bones of Nigerians. Methods: Fragments of non-pathologic bone samples were collected during orthopaedic procedures. Ground sections were prepared using Modified Frost’s manual method of bone preparation to determine the following histologic parameters; haversian canal diameter (HCD), primary and secondary osteons, number of osteon fragments and non haversian canal as well as haversian canal area (HCA). 29 subjects aged 35 to 85 years were used for the study. Bone fragments included samples from the femur, tibia, humerus, and the vertebrae. Data obtained were subjected to descriptive statistics, Pearson’s correlation, bivariate regression equation, student t-test and Analysis of variance (ANOVA). Results: The mean age for our population was 58.86 years. ANOVA shows significant variation in the average HCD for the various regions: humerus=8.45±2.48, femur=7.09±4.06, tibia=8.70±2.52 and vertebrae=3.69±0.73. There is a strong inverse relationship between age and primary osteons. The total number of osteon fragments increased with age while total number of primary osteons and average HCD decreased with age. The HCA though statistically insignificant, also decreased with age. Conclusion: Our findings show that three histomorphometric parameters showed significant correlation with age: osteon fragments (OS-f), primary osteons (OS-p) and HCD. The histomorphometric parameters are therefore relevant in age estimation. Key words: Age estimation, Histomorphometric parameters, Nigerians, Forensics