A survey and cause analysis of community resilience in a Chinese city from the perspective of nursing

Background Community resilience, which fully reflects the ability of communities to resist, absorb, recover or adapt to disasters, has attracted international attention. Nurses are an important force in disaster prevention, relief and postdisaster reconstruction. This study aims to test the current level of community resilience in Dujiangyan city, which was seriously damaged by the Wenchuan earthquake, and analyze the causes. Methods Community data from 952 residents, 574 families, 5 health care institutions and 12 communities in Dujiangyan city were collected by using stratified, cluster, map and systematic sampling methods. A new community resilience evaluation system from the perspective of nursing was used to test individual, family, health care and environmental resilience. Results In Dujiangyan city, average scores were obtained for community resilience (3.93 ± 0.12), individual resilience (4.07 ± 0.64), family resilience (4.07 ± 0.6), health care resilience (3.84 ± 0.33) and community environment resilience (3.69 ± 0.46). Conclusions The urban communities in Dujiangyan city had acceptable resilience, with good family and individual resilience and medium health care and community environment resilience, but environmental resilience had the lowest score. Because conditions and resilience levels varied among the communities, targeted measures should be taken to improve resilience based on population characteristics, management, professional organizations, hardware and software facilities.

Spatial inequalities in skilled birth attendance in India: a spatial-regional model approach

Background Despite a significant increase in the skilled birth assisted (SBA) deliveries in India, there are huge gaps in availing maternity care services across social gradients - particularly across states and regions. Therefore, this study applies the spatial-regression model to examine the spatial distribution of SBA across districts of India. Furthermore, the study tries to understand the spatially associated population characteristics that influence the low coverage of SBA across districts of India and its regions. Methods The study used national representative cross-sectional survey data obtained from the fourth round of National Family Health Survey, conducted in 2015-16. The effective sample size was 259,469 for the analysis. Moran’s I statistics and bivariate Local Indicator for Spatial Association maps were used to understand spatial dependence and clustering of deliveries conducted by SBA coverage in districts of India. Ordinary least square, spatial lag and spatial error models were used to examine the correlates of deliveries conducted by SBA. Results Moran’s I value for SBA among women was 0.54, which represents a high spatial auto-correlation of deliveries conducted by SBA over 640 districts of India. There were 145 hotspots for deliveries conducted by SBA among women in India, which includes almost the entire southern part of India. The spatial error model revealed that with a 10% increase in exposure to mass media in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Interestingly, also with the 10% increase in the four or more antenatal care (ANC) in a particular district, the deliveries conducted by SBA increased significantly by 2.5%. Again, if there was a 10% increase of women with first birth order in a particular district, then the deliveries conducted by SBA significantly increased by 6.1%. If the district experienced an increase of 10% household as female-headed, then the deliveries conducted by SBA significantly increased by 1.4%. Conclusion The present study highlights the important role of ANC visits, mass media exposure, education, female household headship that augment the use of an SBA for delivery. Attention should be given in promoting regular ANC visits and strengthening women’s education.

Epidemics from the population perspective

Many epidemics consist in individuals spreading infection to others. From the population perspective, they also have population characteristics important in modeling, explaining and intervening in epidemics. I analyze epidemiology’s contemporary population perspective through the example of epidemics by examining two central principles attributed to Geoffrey Rose: a distinction between the causes of cases and the causes of incidence, and between ‘high-risk’ and ‘population’ strategies of prevention. Both principles require revision or clarification to capture the sense in which they describe distinct perspectives on the same phenomenon (such as an epidemic), each perspective capturing a different level of contrastive analysis.

Establishment of a New Equation for Ultrasonographic Estimated Foetal Weight in Chongqing: a Prospective Study

Background: Variations in foetal growth between populations should not be ignored, and a single universal standard is not appropriate for everyone. Therefore, it is necessary to develop a new ultrasound estimation equation that adapts better to regional population characteristics. The purpose of this study was to create a new equation for ultrasound estimation of foetal weight according to the local population in Chongqing and compare it with representative equations. Methods: This prospective study included data on pregnant women who gave birth to a child at full term in our hospital from December 2016 to November 2019. Foetal ultrasound parameters included biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur diaphysis length (FDL). The foetal weight compensation model was established by using the second-order linear regression model, and then, the foetal weight equation was established by utilizing the multiple reverse elimination regression technique. Last, the absolute error and relative error were used to compare the accuracy of the equations established in this study with representative equations. Results: Through the foetal weight compensation equation, the new equation suitable for Chongqing foetuses was successfully established with the variables of BPD, HC, AC, and FDL. The following foetal weight prediction equation was established in this study: Log 10 (EFW)=3.002741+0.00005944*(BPD^2)+0.00000222*(HC^2)-0.000002078*(AC^2)+0.00004262*(FDL^2)-0.008753*BPD-0.000884*HC+0.003206*AC-0.002894*FDL (BPD: mm; HC: mm; AC: mm; FDL: mm). In the sets established by the 1925 data, the mean absolute error and standard deviation of the estimation error of the new equation were 178.9 g and 140.3 g respectively. In the validation sets established with 300 data points, the mean absolute error and standard deviation of the new equation were 173.08 g and 128.59 g respectively. Compared with representative equations, the mean absolute error and the standard deviation of the new equation were the lowest. The equation established in this study better predicted foetal weight(P<.001). Conclusions: According to the local population characteristics of Chongqing, this study created a foetal weight estimation equation that is more accurate and suitable. This equation is clinically valuable for the monitoring and management of foetal weight.

Open-access database of literature derived drug-related Torsade de Pointes cases

Since an introduction of an ICH guidance in 2005, no new drugs were withdrawn from the market because of the causation of Torsade de Pointes (TdP). However, the risk of TdP is still a concern for marketed drugs. TdP is a type of polymorphic ventricular tachycardia which may lead to sudden cardiac death. QT/QTc interval prolongation is considered a sensitive, but not specific biomarker. To improve the effectiveness of studies’ workflow related to TdP risk prediction we created an extensive, structured, open-access database of drug-related TdP cases. PubMed, Google Scholar bibliographic databases, and the Internet, via the Google search engine, were searched to identify eligible reports. A total of 424 papers with a description of 634 case reports and observational studies were included. Each paper was manually examined and listed with up to 53 variables related to patient/population characteristics, general health parameters, used drugs, laboratory measurements, ECG results, clinical management, and its outcomes, as well as suspected drug’s properties and its FDA adverse reaction reports. The presented database may be considered as an extension of the recently developed and published database of drug cardiac safety-related information, part of the tox-portal project providing resources for cardiac toxicity assessment.

An Improved Method of Automated Nonparametric Content Analysis for Social Science

Some scholars build models to classify documents into chosen categories. Others, especially social scientists who tend to focus on population characteristics, instead usually estimate the proportion of documents in each category—using either parametric “classify-and-count” methods or “direct” nonparametric estimation of proportions without individual classification. Unfortunately, classify-and-count methods can be highly model-dependent or generate more bias in the proportions even as the percent of documents correctly classified increases. Direct estimation avoids these problems, but can suffer when the meaning of language changes between training and test sets or is too similar across categories. We develop an improved direct estimation approach without these issues by including and optimizing continuous text features, along with a form of matching adapted from the causal inference literature. Our approach substantially improves performance in a diverse collection of 73 datasets. We also offer easy-to-use software that implements all ideas discussed herein.

Time-Varying Stock-Recruitment Model For Estimating Population Characteristics of Green Turtles

The stock-recruitment relationship (SR), customarily used in fisheries assessment, can be used to analyze demographic data of sea turtles to infer changes in hatchling production (R) as a function of nester abundance (S), recruitment rates and the influence of environmental conditions on these population features. The SR Cushing model (R=aS^b), where a and b are the model parameters) is well-suited for representing the dynamics of recovering populations, such as the green turtle (Chelonia mydas) in Campeche, Mexico. This study aimed to explore the SR Cushing model using a time series of the abundance of nesters and hatchlings (1984–2020). By applying local regressions (9-yr moving windows), we found that the time series of parameter b (the change in R as a function of S) and the recruitment rate (hatchlings per nester) were inversely correlated with a 26-yr cycle of the Atlantic Multidecadal Oscillation –sea surface temperature (SST), over the Atlantic– (r^2=0.83) and (r^2=0.64), respectively, at a 3-yr lag). Model diagnostics using the time-dependent Cushing model substantiated that the log-normal distribution of hatchlings of C. mydas in Campeche depends on the abundance of nesting females and on a low frequency SST signal (r^2=0.98). The positive trend in nester numbers of green turtles in Campeche during the past 44 years may be the result of persistent conservation efforts, while the drastic and sporadic changes in the growth rate of annual arrivals and hatchling production are suggestive of population dynamics driven by low frequency, basin-wide environmental signals.

Trends and Determinants of Underweight among Children under Five Years in Ethiopia: Further Analysis with Ethiopian Demographic and Health Survey 2005–2016—Multivariate Decomposition Analysis

Background. Underweight is one of the paramount major worldwide health problems, and it traces a big number of populations from infancy to old age. This study aimed to analyze the trends and predictors of change in underweight among children under five years in Ethiopia. Method. The data for this study were accessed from three Ethiopian Demographic and Health Survey data sets 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. Perceiving the overall trend, the rate of underweight was decreased from 38% in 2005 to 24% in 2016. The decomposition analysis results revealed that, about 12.60% of declines in underweight have been explained by the difference in population characteristics or endowments (E) over the study period. The size of the child at birth, husband’s education, women’s education, and household wealth index contributed significantly to the compositional decline in underweight. Conclusion. The magnitude of underweight among children under five years indicates a remarkable decline over the last ten years in Ethiopia. In this study, two-twelfth of the overall decrease in underweight among children under five years over the decade was due to the difference in characteristics between 2005 and 2016. Continuing to educate the population and boost the population’s economy is needed on the government side in Ethiopia.

Myelin Oligodendrocyte Glycoprotein Antibody Associated Cerebral Cortical Encephalitis: Case Reports and Review of Literature

Myelin oligodendrocyte glycoprotein antibody-associated disease is an immune-mediated demyelinating disease of the central nervous system that is present in both adults and children. The most common clinical manifestations are optic neuritis, myelitis, acute disseminated encephalomyelitis, and brainstem syndrome. Cerebral cortical encephalitis (CCE) is a rare clinical phenotype of myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), which usually begins with seizures, headaches, and fever, and may be misdiagnosed as viral encephalitis in the early stages. Herein, we report two typical MOG antibody (MOG-Ab)-positive patients presenting with CCE, both of whom presented with headache, fever, seizures, and who recovered completely after immunotherapy. In addition, we performed a systematic review of the present literature from the perspectives of population characteristics, clinical symptoms, MRI abnormalities, treatments, and prognosis. Among the patients reported in 25 articles, 33 met our inclusion criteria, with the age of onset ranging from 4 to 52 years. Most of the patients had seizures, headache, fever, and unilateral cortical lesions on brain MRI. For acute CCE, 30 patients were treated with high-dose intravenous methylprednisolone, and the symptoms of most patients were completely relieved after immunotherapy. This study reported our experience and lessons learned in the diagnosis and treatment of MOG-Ab-positive CCE and provides a systematic review of the literature to analyse this rare clinical phenotype.