Persistent organic pollutants distribution in plasma lipoprotein fractions

This study determines the associations among serum lipid profiles, risk of cardiovascular disease, and persistent organic pollutants. Using Gas chromatography technique, the intensity of toxic pollutant residues in serum samples of Hypertensive patients were measured. Based on statistical analysis, the effects of different covariates namely pesticides, age, systolic blood pressure, diastolic blood pressure, and lipid profile duration was checked using the logistic regression model. Statistical computation was performed on SPSS 22.0. The P-values of F-Statistic for each lipid profile class are greater than 0.01 (1%), therefore we cannot reject the null hypothesis for all cases. The estimated coefficients, their standard errors, Wald Statistic, and odds ratio of the binary logistic regression model for different lipid profile parameters indicate if pesticides increase then the logit value of different lipid profile parameters changes from -0.46 to -0.246 except LDL which increases by 0.135. The study reports a significantly increased threat of cardiovascular disease with increased concentrations of toxic pollutants.

A Statistical Intra-Seasonal Prediction Model of Extended Boreal Summer Western North Pacific Tropical Cyclone Genesis

A L2 regularized logistic regression model is developed in this study to predict weekly tropical cyclone (TC) genesis over the western North Pacific (WNP) and sub-regions of the WNP including the South China Sea (SCS), the western WNP (WWNP), and the eastern WNP (EWNP). The potential predictors for the TC genesis model include a time-varying TC genesis climatology, the Madden-Julian oscillation (MJO), the quasi-biweekly oscillation (QBWO), and ENSO. The relative importance of the predictors in a constructed L2 regression model is justified by a forward stepwise selection procedure for each region from a 0-week to a 7-week lead. Cross-validated hindcasts are then generated for the corresponding prediction schemes out to a 7-week lead. The TC genesis climatology generally improves the regional model skill, while the importance of intra-seasonal oscillations and ENSO are regionally dependent. Over the WNP, there is increased model skill over the time-varying climatology in predicting weekly TC genesis out to a 4-week lead by including the MJO and QBWO, while ENSO has a limited impact. On a regional scale, ENSO and then the MJO and QBWO respectively, are the two most important predictors over the EWNP and WWNP after the TC genesis climatology. The MJO is found to be the most important predictor over the SCS. The logistic regression model is shown to have comparable reliability and forecast skill scores to the ECMWF dynamical model on intra-seasonal time scales.

Prevalence and factors affecting the utilization of antenatal care in rural areas of Southwestern Ethiopia

Background Antenatal care (ANC) is a health care intervention intended to ensure the safety of pregnancy. According to the World Health Organization, at least four ANC visits are recommended for a healthy pregnancy. However, whether this recommended number of visits was followed or not in the rural areas of Southwestern Ethiopia is not known. Therefore, the study aimed to investigate the prevalence of, and the associated factors of ANC utilization by pregnant women in the rural areas of Southwestern Ethiopia. Methods A community-based cross-sectional study design was used in three rural zones. The data were collected from n = 978 women through a structured questionnaire with face-to-face interview. The collected data were analyzed using descriptive statistics and a multiple binary logistic regression model. Results The results showed that 56% of women made the recommended minimum number of ANC visits and the remaining 44% of them underutilized the ANC service. The multiple binary logistic regression model identified zone, marital status of the woman, educational level of the husband, occupation of the husband, knowledge of danger signs of pregnancy, birth interval, source of information, timely visits, and transportation problem to be statistically significant factors affecting the prevalence of ANC visit utilization of women. Bench Maji zone had smaller odds ratio of ANC visit prevalence as compared to Kaffa zone. Women who lived in the rural area of Sheko zone are 2.67 times less likely to utilize ANC visit than those who lived in the rural area of Kaffa zone keeping other variables constant. Conclusion The study results highlight the need to increase the number of ANC visits, and the importance of using an appropriate model to determine the important socio-demographic factors that ANC service providers shall focus on to improve the health of the unborn baby and the mother during pregnancy.

CEO Information Ability, Absorptive Capacity, and E-Commerce Adoption among Small, Medium, and Micro Enterprises in China

The purpose of this study was to explore the relationship between chief executive officer (CEO) characteristics, absorptive capacity, and e-commerce adoption in SMMEs. To achieve this objective, the study analyzed primary data gathered from 2675 small, medium, and micro enterprises (SMMEs) in China. A logistic regression model was employed to estimate how the CEO characteristics and absorptive capacity of SMMEs influenced their e-commerce adoption. The study revealed a significant positive relationship between CEO information ability, confidence, and e-commerce adoption. Additionally, this study confirmed a positive relationship between absorptive capacity and the adoption of e-commerce.

Determinants of Regional Economic Resilience to Economic Crisis: Evidence from Chinese Economies

The severity of the 2007–2008 economic crisis and the spatial heterogeneity of its impact have accelerated the study of regional economic resilience. The economic crisis has affected most parts of the world, and its impact is highly heterogeneous within China. The aim of this study was to explore the determinants of regional economic resilience across 284 Chinese cities from 2003–2018. Both nation-based and province-based regional economic resilience were examined. A multilevel logistic regression model was established, finding a disparity of provincial effects on regional performance during the economic crisis. Regional economic resilience is significantly affected by provincial trajectories, economy size, and resources. There are five significant determinants of economic resilience: income inequality, innovation, government intervention, human capital, and financial development. The results provide evidence for the government to design region-based policies, taking into consideration the size and the resources of the region’s economy to build a resilient wall to defend against external shocks and to form a basis for sustainable development.

Choroidal Thickness and Granulocyte Colony-Stimulating Factor in Tears Improve the Prediction Model for Coronary Artery Disease

Background: Coronary artery disease (CAD) detection in asymptomatic patients still remains controversial. The aim of our study was to evaluate the usefulness of ophthalmologic findings as predictors of the presence of CAD when added to cardiovascular classic risk factors (CRF) in patients with acute coronary cardiopathy suspicion. Methods: After clinical stabilization, 96 patients with acute coronary cardiopathy suspicion were selected and divided in two groups: 69 patients with coronary lesions and 27 patients without coronary lesions. Their 192 eyes were subjected to a complete routine ophthalmologic examination. Samples of tear fluid were also collected to be used in the detection of cytokines and inflammatory mediators. Logistic regression models, receiver operating characteristic curves and their area under the curve (AUC) were analysed. Results: Suggestive predictors were choroidal thickness (CT) (OR: 1.02, 95% CI: 1.01-1.03) and tear granulocyte colony-stimulating factor (G-CSF) (OR: 0.97, 95% CI: 0.95-0.99). We obtained an AUC of 0.9646 (95% CI: 0.928-0.999) when CT and tear G-CSF were added as independent variables to the logistic regression model with cardiovascular CRF: sex, age, diabetes, high blood pressure, hypercholesterolemia, smoking habit and obesity. This AUC was significantly higher (p=0.003) than the prediction derived from the same logistic regression model without CT and tear G-CSF (AUC=0.828, 95% CI: 0.729-0.927). Conclusions: CT and tear G-CSF improved the predictive model for CAD when added to cardiovascular CRF in our sample of symptomatic patients. Subsequent studies are needed for validation of these findings in asymptomatic patients.

Timely initiation of antenatal care and its associated factors among pregnant women in sub-Saharan Africa: A multicountry analysis of Demographic and Health Surveys

Background Timely initiation of antenatal care (ANC) is an important component of ANC services that improve the health of the mother and the newborn. Mothers who begin attending ANC in a timely manner, can fully benefit from preventive and curative services. However, evidence in sub-Saharan Africa (sSA) indicated that the majority of pregnant mothers did not start their first visit timely. As our search concerned, there is no study that incorporates a large number of sub-Saharan Africa countries. Thus, the objective of this study was to assess the prevalence of timely initiation of ANC and its associated factors in 36 sSA countries. Methods The Demographic and Health Survey (DHS) of 36 sSA countries were used for the analysis. The total weighted sample of 233,349 women aged 15–49 years who gave birth in the five years preceding the survey and who had ANC visit for their last child were included. A multi-level logistic regression model was used to examine the individual and community-level factors that influence the timely initiation of ANC. Results were presented using adjusted odds ratio (AOR) with 95% confidence interval (CI). Results In this study, overall timely initiation of ANC visit was 38.0% (95% CI: 37.8–38.2), ranging from 14.5% in Mozambique to 68.6% in Liberia. In the final multilevel logistic regression model:- women with secondary education (AOR = 1.08; 95% CI: 1.06, 1.11), higher education (AOR = 1.43; 95% CI: 1.36, 1.51), women aged 25–34 years (AOR = 1.20; 95% CI: 1.17, 1.23), ≥35 years (AOR = 1.30; 95% CI: 1.26, 1.35), women from richest household (AOR = 1.19; 95% CI: 1.14, 1.22), women perceiving distance from the health facility as not a big problem (AOR = 1.05; 95%CI: 1.03, 1.07), women exposed to media (AOR = 1.29; 95%CI: 1.26, 1.32), women living in communities with medium percentage of literacy (AOR = 1.51; 95%CI: 1.40, 1.63), and women living in communities with high percentage of literacy (AOR = 1.56; 95%CI: 1.38, 1.76) were more likely to initiate ANC timely. However, women who wanted their pregnancy later (AOR = 0.84; 95%CI: 0.82, 0.86), wanted no more pregnancy (AOR = 0.80; 95%CI: 0.77, 0.83), and women residing in the rural area (AOR = 0.90; 95%CI: 0.87, 0.92) were less likely to initiate ANC timely. Conclusion Even though the WHO recommends all women initiate ANC within 12 weeks of gestation, sSA recorded a low overall prevalence of timely initiation of ANC. Maternal education, pregnancy intention, residence, age, wealth status, media exposure, distance from health facility, and community-level literacy were significantly associated with timely initiation of ANC. Therefore, intervention efforts should focus on the identified factors in order to improve timely initiation of ANC in sSA. This can be done through the providing information and education to the community on the timing and importance of attending antenatal care and family planning to prevent unwanted pregnancy, especially in rural settings.

The Prevalence of Integument Injuries and Associated Risk Factors Among Canadian Turkeys

Injurious pecking can cause a wide range of damage and is an important welfare and economic issue in turkey production. Aggressive pecking typically targets the head/neck (HN) area, and feather pecking typically targets the back/tail (BT) area; injuries in these separate areas could be used as a proxy for the level of aggressive and feather pecking in a flock. The objective of this study was to identify risk factors for integument injuries in Canadian turkey flocks. A survey containing a questionnaire about housing and management practices and a scoring guide was distributed to 500 turkey farmers across Canada. The farmer scored pecking injuries in two different body areas (HN and BT) on a 0–2 scale on a subset of birds within each flock. Multivariable logistic regression modeling was used to identify factors associated with the presence of HN and BT injuries. The prevalence of birds with integument injuries ranged widely between the flock subsets (HN = 0–40%, BT = 0–97%), however the mean prevalence was low (HN = 6%, BT = 10%). The presence of injuries for logistic regression was defined as flocks with an injury prevalence greater than the median level of injury prevalence in the dataset (3.3% HN and 6.6% BT). The final logistic regression model for HN injuries contained five variables: flock sex, flock age, number of daily inspections, number of different people during inspections, and picking up birds during inspections (N = 62, pR2 = 0.23, α = 0.05). The final logistic regression model for BT injuries contained six variables: flock sex, flock age, litter depth, litter condition, inspection duration, and use of hospital pens for sick/injured birds (N = 59, pR2 = 0.29, α = 0.05). Flock age, and to a lesser extent, sex was associated with both types of injuries. From a management perspective, aggressive pecking injuries appear to be influenced by variables related to human interaction, namely during inspections. On the other hand, the presence of feather pecking injuries, was associated with litter condition and other management factors like separating sick birds. Future research on injurious pecking in turkeys should focus on these aspects of housing and management to better describe the relationship between the identified variables and the prevalence and severity of these conditions.

Probability Density Function Analysis Based on Logistic Regression Model

The data fitting level in probability density function analysis has great influence on the analysis results, so it is of great significance to improve the data fitting level. Therefore, a probability density function analysis method based on logistic regression model is proposed. The logistic regression model with kernel function is established, and the optimal window width and mean square integral error are selected to limit the solution accuracy of probability density function. Using the real probability density function, the probability density function with the smallest error is obtained. The estimated probability density function is analyzed from two aspects of consistency and convergence speed. The experimental results show that compared with the traditional probability density function analysis method, the probability density function analysis method based on logistics regression model has a higher fitting level, which is more suitable for practical research projects.

Prevalence of, and risk factors for, cognitive impairment in lacunar stroke

Background: Small vessel disease (SVD) is associated with vascular cognitive impairment (VCI) but why VCI occurs in some, but not other patients, is uncertain. We determined the prevalence of, and risk factors for, VCI in a large cohort of patients with lacunar stroke. Methods: Participants with magnetic resonance imaging (MRI)-confirmed lacunar stroke were recruited in the multicenter DNA Lacunar 2 study and compared with healthy controls. A logistic regression model was used to determine which vascular risk factors and MRI parameters were independent predictors of VCI, assessed using the Brief Memory and Executive Test (BMET). Results: A total of 912 lacunar stroke patients and 425 controls were included, with mean ( SD) age of 64.6 (12.26) and 64.7 (12.29) years, respectively. VCI was detected in 38.8% lacunar patients and 13.4% controls. In a logistic regression model, diabetes mellitus (odds ratio (OR) = 1.98 (95% confidence interval (CI) = 1.40–2.80), p < 0.001) and higher body mass index (BMI) (OR = 1.03 (95% CI = 1.00–1.05), p = 0.029) were independently associated with increased risk of VCI, and years of full-time education with lower risk (OR = 0.92 (95% CI = 0.86–0.99), p = 0.018). When entering both lacune count and white matter hyperintensity (WMH) in the same logistic regression model, only WMH grade was significantly associated with VCI (OR = 1.46 (95% CI = 1.24–1.72), p < 0.001). Conclusion: VCI is common in lacunar stroke patients, affecting almost 40%. This prevalence suggests that it should be routinely screened for in clinical practice. Risk factors for VCI in patients with lacunar stroke include diabetes mellitus, depressive symptoms, higher BMI, and WMH severity, while education is protective.