An Ecosystemic Approach to Preventing Bullying in School. Risk Factors Associated with School

Previous research has shown that teachers play an important role in preventing bullying in school. Nowadays, there is a growing interest in understanding the risk factors associated with school such as the teachers’ perception of the severity of bullying and their response to bullies and victims. This paper presents risk factors associated with bullying and teachers’ perceptions within Bronfenbrenner’s (1977) classic ecological theory.According to this paradigm, changes are required in the environments with which children interact as they develop (family, school, community and society). By exposing the factors that trigger and maintain bullying, we aim to highlight the importance of Bronfenbrenner's ecological systems model in designing bullying prevention strategies. We will focus on the risk factors associated with school, chief among which is the, teachers' perceptions of bullying in school. Not only does this view contribute to optimizing the understanding of the importance of ecosystem theory for effectiveness prevention, but it also suggests that both research and prevention should focus on individual risk factors that influence teachers' reactivity to bullying behaviors.

How Accurate are Geriatricians’ Fall Predictions?

Background: Older patients are at increased risk of falling and of serious morbidity and mortality resulting from falls. The ability to accurately identify older patients at increased fall risk affords the opportunity to implement interventions to reduce morbidity and mortality. Geriatricians are trained to assess older patients for fall risk. If geriatricians can accurately predict fallers (as opposed to evaluating for individual risk factors for falling), more aggressive and earlier interventions could be employed to reduce falls in older adult fallers. However, there is paucity of knowledge regarding the accuracy of geriatrician fall risk predictions. This study aims to determine the accuracy of geriatricians in predicting falls. Methods: Between October 2018 and November 2019, a convenience sample of 100 subjects was recruited from an academic geriatric clinic population seeking routine medical care. Subjects performed a series of gait and balance assessments, answered the Stay Independent Brochure and were surveyed about fall incidence 6-12 months after study entry. Five geriatricians, blinded to subjects and fall outcomes, were provided the subjects’ data and asked to categorize each as a faller or non-faller. No requirements were imposed on the geriatricians’ use of the available data. These predictions were compared to predictions of an examining geriatrician who performed the assessments and to fall outcomes reported by subjects. Results: Kappa values for the 5 geriatricians who used all the available data to classify participants as fallers or non-fallers compared with the examining geriatrician were 0.42 to 0.59, indicating moderate agreement. Compared to screening tools’ mean accuracy of 66.6% (59.6-73.0%), the 5 geriatricians had a mean accuracy for fall prediction of 67.4% (57.3-71.9%).Conclusions: This study adds to the scant knowledge available in the medical literature regarding the abilities of geriatricians to accurately predict falls in older patients. Studies are needed to characterize how geriatrician assessments of fall risk compare to standardized assessment tools.

DETERMINANTS OF NEET (NOT IN EMPLOYMENT, EDUCATION OR TRAINING) ON THE POLISH LABOUR MARKET

The principal purpose of the study is to identify the individual risk factors of young people becoming the NEET generation on the Polish labour market. The first part of the paper comprises a literature-based overview of definitions of the NEET category based and a presentation of the risk factors of young people becoming NEET. The second part presents the results of empirical analyses conducted employing a questionnaire on a group of 120 individuals, aged 15 through 30, who met all criteria of the NEET definition set forth by the Employment Committee of the EU. The research demonstrates that among the major determinants of young people becoming NEET are financial hardship of their households, low motivation to continue formal education or change professional qualifications, and low level of job-seeking activity.

COVID-19 severity prediction based on patient risk factors and number of vaccines received

Background Vaccines are highly effective in preventing severe disease and death from COVID-19, and new medications that can reduce severity of disease have been approved. However, many countries are facing limited supply of vaccine doses and medications. A model estimating the probabilities for hospitalization and mortality according to individual risk factors and vaccine doses received could help prioritize vaccination and yet scarce medications to maximize lives saved and reduce the burden on hospitalization facilities. Methods Electronic health records from 101,034 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until November 30, 2021 were extracted from a national healthcare organization in Israel. Logistic regression models were built to estimate the risk for subsequent hospitalization and death based on the number of BNT162b2 mRNA vaccine doses received and few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and presence of hypertension, pulmonary disease or malignancy). Results The models built predict the outcome of newly infected individuals with remarkable accuracy: area under the curve was 0.889 for predicting hospitalization, and 0.967 for predicting mortality. Even when a breakthrough infection occurs, having received three vaccination doses significantly reduces the risk of hospitalization by 66% (OR=0.336) and of death by 78% (OR=0.220). Conclusions The models enable rapid identification of individuals at high risk for hospitalization and death when infected. These patients can be prioritized to receive booster vaccination and the yet scarce medications. A calculator based on these models is made publicly available on http://covidest.web.app

Modern approaches to prevention of non-communicable diseases in the state program of healthcare development of the Republic of Kazakhstan

Problems of prevention of noncommunicable diseases are relevant for many countries of the world. This is due to the fact that the burden of noncommunicable diseases is growing from year to year, creating new challenges to the health systems of various countries. To address these problems, various programs are being implemented, both defining General prevention strategies across the country, and programs to combat individual risk factors. The article presents an analysis of programs aimed at fighting cancer, implemented in various countries. The essence analysis of the program showed that the main tasks, key priorities and directions of the state program for health development of the Republic of Kazakhstan “Salamatty Kazakhstan” (Healthy Kazakhstan) for 2011–2015 were formed and implemented taking into account the trends of economic, social and demographic development of the country. The usefulness of this complex intersectoral organizational technology for strengthening public health at the national level is shown, and evidence of the effectiveness of the program is provided.

Comparative Analysis of Obstetric Hemorrhage Risk Prediction Tools

Objective Hemorrhage risk prediction tools were developed in response to rising rates of obstetric hemorrhage (OBH). The California Maternal Quality Care Collaborative (CMQCC) risk prediction tool classifies patients as low, medium, and high risk for OBH based on individual risk factors. At our institution, Magee-Womens Hospital (MWH), a unique OBH risk prediction tool was derived from the CMQCC tool that differs through its use of weighted risk factors and distinctive laboratory value cutoffs. Our objective is to compare this enhanced institution-specific tool to the CMQCC tool. Study Design This study was a retrospective cohort analysis of delivery admissions from a single health care network. Admission OBH risk scores were assigned to each patient using both the MWH and CMQCC scores. Cohen's kappa estimated agreement. Scoring systems and maternal outcomes were compared using chi-square test. Composite morbidity included transfusion, hysterectomy, uterine artery embolization, and intensive care unit admission. Results A total of 21,843 delivery admissions were included. A moderate association was observed between scoring systems (kappa 0.41, p < 0.001). The CMQCC tool categorized 16,184 (74%) patients as low risk, 4,664 (21%) as medium risk, and 995 (5%) as high risk. The MWH tool categorized 13,137 (60%) patients as low risk, 8,113 (37%) as medium risk, and 593 (3%) as high risk. The MWH score recategorized CMQCC low-risk patients to a higher stratum 26% of the time. CMQCC high-risk patients were recategorized to a lower stratum 82% of the time. Both the MWH and CMQCC tools were able to differentiate OBH-related morbidity across risk strata. The MWH tool independently predicted risk of composite morbidity within each stratum of the CMQCC score. Conclusion Both the MWH and CMQCC tools independently distinguish risk of composite morbidity. Adding weighted values to individual risk factors further discriminates risk of morbidity. This suggests it may be reasonable to adapt the CMQCC tool to reflect institutional populations and resources. Key Points

‘Genetics load the gun, but the environment pulls the trigger’: novel, emerging and non-traditional risk factors in cardiovascular disease

In this article, Andy Richardson, BANCC Educational Advisor, examines several important environmental and individual risk factors for cardiovascular disease. Following on from the meeting of Global Leaders at COP26 in Glasgow, he considers the impact of, and exposure to, environmental factors, including pollution and noise.

Trends and associated factors for Covid-19 hospitalisation and fatality risk in 2.3 million adults in England

Background The Covid-19 case fatality ratio varies between countries and over time but it is unclear whether variation is explained by the underlying risk in those infected. This study aims to describe the trends and risk factors for admission and mortality rates over time in England. Methods In this retrospective cohort study, we included all adults (≥18 years) in England with a positive Covid-19 test result between 1st October 2020 and 30th April 2021. Data were linked to primary and secondary care electronic health records and death registrations. Our outcomes were i) one or more emergency hospital admissions and ii) death from any cause, within 28 days of a positive test. Multivariable multilevel logistic regression was used to model each outcome with patient risk factors and time. Results 2,311,282 people were included in the study, of whom 164,046 (7.1%) were admitted and 53,156 (2.3%) died within 28 days. There was significant variation in the case hospitalisation and mortality risk over time, peaking in December 2020-February 2021, which remained after adjustment for individual risk factors. Older age groups, males, those resident in more deprived areas, and those with obesity had higher odds of admission and mortality. Of risk factors examined, severe mental illness and learning disability had the highest odds of admission and mortality. Conclusions In one of the largest studies of nationally representative Covid-19 risk factors, case hospitalisation and mortality risk varied significantly over time in England during the second pandemic wave, independent of the underlying risk in those infected.

P-P02 Incidence and risk factors for chyle leak after pancreatic surgery: a systematic review and meta-analysis

Background The incidence of, and risk factors for chyle leak, as defined by the 2017 International Study Group on Pancreatic Surgery (ISGPS), remain unknown. Methods MEDLINE, EMBASE, and Scopus were systematically searched for studies of patients undergoing pancreatectomy that reported chyle leak according to the 2017 ISGPS definition. The primary outcomes were the incidence of overall and clinically-relevant chyle leak. A random-effects pairwise meta-analysis was used to identify risk factors where possible. Results Thirty-five studies including 7083 patients were included in the meta-analysis. The weighted incidence of overall chyle leak was 6.8% (95% CI 5.6 - 8.2) and clinically-relevant chyle leak was 5.5% (95% CI 3.8 - 7.7). Pancreaticoduodenectomy, total pancreatectomy and distal pancreatectomy were associated with a CL incidence of 7.3%, 4.3%, 5.8% respectively. Fourteen individual risk factors for chyle leak were identified from included studies. Younger age, low prognostic nutritional index, para-aortic node manipulation, lymphatic involvement, and post-pancreatectomy pancreatitis were significantly associated with chyle leak, all from individual studies. Conclusions The incidence of overall chyle leak and clinically relevant chyle leak after pancreatic surgery, as defined by the 2017 ISGPS definition is 6.8% and 5.5% respectively. Several risk factors for chyle leak were identified in the present review, however, larger high-quality studies are needed to more accurately define these risks.

Community versus individual risk of SARS-CoV-2 infection in two municipalities of Louisiana, USA: An assessment of Area Deprivation Index (ADI) paired with seroprevalence data over time

Objective Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors. Study design and setting 4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection. Results In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant. Conclusions While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.