Risk Events Research Articles

Infectious risk events and their novelty in event-based surveillance: new definitions and annotated corpus

Infectious risk events and their novelty in event-based surveillance: new definitions and annotated corpus

Association between long-term use of calcium channel blockers (CCB) and the risk of breast cancer: a retrospective longitudinal observational study protocol

IntroductionCalcium channel blockers (CCB), a commonly prescribed antihypertensive (AHT) medicine, may be associated with increased risk of breast cancer. The proposed study aims to examine whether long-term CCB use is...

Logical ontological modeling of cargo port risk management

Enterprises in any field, including those in the transport and logistics sector, are faced with the need to gain a competitive advantage through the use of innovative management methods. These include the integrated use of methods for managing organizational systems along with the use of advanced tools and technologies. Particular attention is paid to risk management in order to prevent undesirable situations. This paper is the first to present a description of a logical ontological model for the integrated application of multi-level goal setting based on a balanced scorecard (BSC) and logical probabilistic (LP) modeling to support decision-making on cargo port risk management. Situations of failure to achieve the goals of the cargo port, including failure to achieve standard values of indicators, are considered as risks. The integrated use of BSC and LP modeling technologies made it possible to build a general concept of multi-level goal setting. Its main advantage lies in the detailed elaboration of the company’s goals, which are subordinated to the main strategic goal. This makes it possible to influence operational events and obtain positive results in tactical and strategic plans. The ontological model contains all the information about the components interaction that influence the risk events and makes it possible to select options for exiting a risk situation in accordance with specified conditions. The results of queries to a risk-oriented ontological model are options for management decisions aimed at reducing risks in the operation of a cargo port.

Joint modeling of longitudinal and competing risks for assessing blood oxygen saturation and its association with survival outcomes in COVID-19 patients.

The objective of the present study is to evaluate the association between longitudinal and survival outcomes in the presence of competing risk events. To illustrate the application of joint modeling in clinical research, we assessed the blood oxygen saturation (SPO2) and its association with survival outcomes in coronavirus disease (COVID-19). In this prospective cohort study, we followed 300 COVID-19 patients, who were diagnosed with severe COVID-19 in the Rohani Hospital in Babol, the north of Iran from October 22, 2020 to March 5, 2021, where death was the event of interest, surviving was the competing risk event and SPO2 was the longitudinal outcome. Joint modeling analyses were compared to separate analyses for these data. The estimation of the association parameter in the joint modeling verified the association between longitudinal outcome SPO2 with survival outcome of death (Hazard Ratio (HR) = 0.33, P = 0.001) and the competing risk outcome of surviving (HR = 4.18, P < 0.001). Based on the joint modeling, longitudinal outcome (SPO2) decreased in hypertension patients (β = -0.28, P = 0.581) and increased in those with a high level of SPO2 on admission (β = 0.75, P = 0.03). Also, in the survival submodel in the joint model, the risk of death survival outcome increased in patients with diabetes comorbidity (HR = 4.38, P = 0.026). The association between longitudinal measurements of SPO2 and survival outcomes of COVID-19 confirms that SPO2 is an important indicator in this disease. Thus, the application of this joint model can provide useful clinical evidence in the different areas of medical sciences.

Mitigasi Risiko Pengadaan Bahan Baku di PT Inalum dengan Metode House of Risk (HOR)

PT Inalum is a company specializing in aluminum production, focusing on smelting business and raw material development into aluminum. Annually, PT Inalum produces approximately 250 thousand tons of aluminum. The procurement of primary raw materials plays a significant role in its production chain. Delay in the delivery of primary raw materials can hinder aluminum production. The aim of this research is to identify the risks that may affect the arrival of primary raw materials at PT Inalum and to develop mitigation strategies to minimize the impact of these risks. The research method used is the House of Risk, consisting of two phases. The first phase involves identifying potential risk events that may affect the arrival of primary raw materials, as well as the involved risk agents. The second phase involves determining the relationship between risk events and risk agents, as well as developing mitigation strategies based on the highest risk ranking. From this research, 35 risk events and 21 risk agents that may affect the arrival of primary raw materials at PT Inalum have been identified. Furthermore, through the analysis of House of Risk phase 2, 7 recommendations for mitigation actions with the highest ranking were obtained, including budget monitoring, inventory management improvement, and enhancement of procurement and logistics procedures. The findings of this research can be implemented in the procurement of primary raw materials at PT Inalum to improve efficiency and reduce the risk of aluminum production delays.

Progressing the research on systemic risk, cascading disasters, and compound events

Disaster risk in the 21st century differs from the experience of past generations and is defined by its evolving systemic nature. The increased role of technological networks, societal interdependencies and climate change dynamics make crises more complex and unpredictable. Cascading and compounding dynamics are becoming the new “business as usual”, challenging emergency management to maintain operations in face of complex disruptions while requiring the development of good practices and strategy for facilitate the recovery process. Our special issue aimed to support the development of a paradigm shift in the understanding of complex events, utilizing a network-based, cross-disciplinary approach to resilience. This editorial introduces and summarizes 18 papers across four thematic areas: 1) Resilience Challenges; 2) Area Studies and the Sendai Framework for Disaster Risk Reduction; 3) Community and Health; 4) Enhancing New Methodologies. The conclusions highlight open research challenges for future exploration.

Research on Risk Contagion in ESG Industries: An Information Entropy-Based Network Approach.

Sustainable development is a practical path to optimize industrial structures and enhance investment efficiency. Investigating risk contagion within ESG industries is a crucial step towards reducing systemic risks and fostering the green evolution of the economy. This research constructs ESG industry indices, taking into account the possibility of extreme tail risks, and employs VaR and CoVaR as measures of tail risk. The TENET network approach is integrated to to capture the structural evolution and direction of information flow among ESG industries, employing information entropy to quantify the topological characteristics of the network model, exploring the risk transmission paths and evolution patterns of ESG industries in an extreme tail risk event. Finally, Mantel tests are conducted to examine the existence of significant risk spillover effects between ESG and traditional industries. The research finds strong correlations among ESG industry indices during stock market crash, Sino-US trade frictions, and the COVID-19 pandemic, with industries such as the COAL, CMP, COM, RT, and RE playing key roles in risk transmission within the network, transmitting risks to other industries. Affected by systemic risk, the information entropy of the TENET network significantly decreases, reducing market information uncertainty and leading market participants to adopt more uniform investment strategies, thus diminishing the diversity of market behaviors. ESG industries show resilience in the face of extreme risks, demonstrating a lack of significant risk contagion with traditional industries.

A Dirichlet process mixture regression model for the analysis of competing risk events

We develop a regression model for the analysis of competing risk events. The joint distribution of the time to these events is flexibly characterized by a random effect which follows a discrete probability distribution drawn from a Dirichlet Process, explaining their variability. This entails an additional layer of flexibility of this joint model, whose inference is robust with respect to the misspecification of the distribution of the random effects. The model is analysed in a fully Bayesian setting, yielding a flexible Dirichlet Process Mixture model for the joint distribution of the time to events. An efficient MCMC sampler is developed for inference. The modelling approach is applied to the empirical analysis of the surrending risk in a US life insurance portfolio previously analysed by Milhaud and Dutang (2018). The approach yields an improved predictive performance of the surrending rates.

Case-based activities for risk management education

PurposeThis study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.Design/methodology/approachThe study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.Findings@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.Originality/valueThe insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

Safety and efficacy of combined dual antiplatelet therapy and factor VIII prophylaxis in patients with haemophilia A after acute coronary syndrome.

The increased life expectancy of patients with haemophilia A (HA) has led to a growing prevalence of cardiovascular risk factors and events. There is still scarce evidence on the safety and appropriate duration of dual antiplatelet therapy (DAPT) after acute coronary syndrome (ACS) in HA patients. We describe our experience on the clinical management of Italian HA patients after ACS. Nine patients with congenital HA treated with DAPT after a revascularization procedure performed for ACS have been enrolled and followed at the Angelo Bianchi Bonomi Haemophilia and Thrombosis Center in Milan between 2005 and September 2022. The safety and efficacy of DAPT with or without FVIII prophylaxis were assessed. Ten ACS events occurred in the nine HA patients (four mild and five severe). All events were treated with percutaneous transluminal coronary angioplasty with deployment of 1 to 3 drug-eluting stents followed by DAPT for 1-12 months. All patients except one were treated with FVIII prophylaxis during DAPT aimed at achieving FVIII trough levels ≥20-30IU/dL. DAPT was effective in all cases in preventing early ACS recurrence, with only a late recurrence. We observed two clinically relevant non-major bleeds (one in a patient without FVIII prophylaxis) and three minor bleeds. No venous thrombosis occurred. The long-term secondary antithrombotic prevention consisting of DAPT and FVIII prophylaxis achieving a trough level of 20-30IU/dL can be effective and safe in HA patients.

Age-Related Risk of Serious Fall Events and Opioid Analgesic Use

Opioid analgesics may be associated with increased risk of falls, particularly among older adults. To quantify the age-related risk of serious fall events among adults prescribed opioids by opioid exposure, time from initiation, and daily dose. This population-based cohort study conducted in New South Wales, Australia, used data linking national pharmaceutical claims to national and state datasets, including information on sociodemographic characteristics, clinical characteristics, medicines use, health services utilization, and mortality (POPPY II study). It included adults (18 years or older) who initiated prescription opioid treatment, which was defined as no prior dispensing during the preceding 365 days, between January 1, 2005, and December 31, 2018. Data were analyzed from February to June 2023. Time-dependent periods of opioid exposure were evaluated from dispensing records. Serious fall events identified from emergency department, hospitalization, and mortality records. Negative binomial models were used to assess associations between time-dependent opioid exposure (overall, by time from initiation, and by dose), age, and risk of fall events. Models were adjusted for known fall risk factors, including other fall risk-increasing drugs, frailty risk, and prior serious fall events. The cohort comprised 3 212 369 individuals who initiated prescription opioid treatment (1 702 332 women [53%]; median [IQR] age at initiation, 49 [32-65] years). Overall, 506 573 serious fall events were identified, including 5210 fatal falls. During exposure to opioids, the risk of serious fall events was elevated among all age groups; compared with the group aged 18 to 44 years, this risk was highest among those 85 years or older (adjusted incident rate ratio, 6.35; 95% CI, 6.20-6.51). Across all age groups, the first 28 days following opioid initiation was a time of increased serious fall risk; this risk increased with age. Among individuals aged 18 to 84 years, associations were identified between higher daily opioid doses and serious fall events. The results of this cohort study suggest that prescription opioids were associated with increased risk of serious fall events among adults of all ages, with individuals 85 years or older at greatest risk. These risks should be considered when prescribing opioids, particularly for individuals with preexisting risk factors or when opioids are prescribed at higher doses. Targeted falls prevention efforts may be most effective within the first month following opioid initiation.

Cumulative incidence and risk factors of brain metastases in metastatic non-small cell lung cancer without baseline brain metastasis: Pooled analysis of individualized patient data from IMpower130, IMpower131, and IMpower150.

The objective of this study was to explore the abilities of atezolizumab plus chemotherapy in preventing brain metastases (BMs) among metastatic non-small cell lung cancer (NSCLC) without initial BMs, as well as the risk factors of BMs. Individual patient data from three trials involving first-line atezolizumab for metastatic NSCLC (IMpower130, IMpower131, and IMpower150) were pooled. Among patients without baseline BMs and without epidermal growth factor receptor(EGFR) and/or anaplastic lymphoma kinase (ALK) mutations, those receiving atezolizumab+chemotherapy±bevacizumab were classified as the atezolizumabplus chemotherapy group and those receiving placebo+chemotherapy±bevacizumab were classified as the chemotherapy group. The cumulative incidences of BM (CI-BMs) between the two groups were compared. Other factors associated with the CI-BM were analyzed by Cox regression analyses. With a median follow-up of 17.6 months (range, 0.03-33.64 months), 74 (3.1%) of the 2380 enrolled patients developed BMs, including 50 (3.1%) and 24 (3.0%) in the atezolizumab plus chemotherapy group (n=1589) and the chemotherapy group (n=791), respectively. The CI-BMs at 6, 12, and 24months were 1.7%, 2.8%, and 3.3%, respectively. After taking competing risk events into account, there was no significant difference in the CI-BMs between the two groups (p=.888). Nevertheless, the use of bevacizumab and the histology of nonsquamous NSCLC were found to be independently associated with the risk of BMs. In patients with metastatic EGFR/ALK wild-type NSCLC without baseline BMs, adding atezolizumab in the first-line treatment might not reduce the CI-BM. However, the administration of bevacizumab may reduce the risk of BMs.

Association between beta-blocker utilization and heart failure mortality in the peritoneal dialysis population: a cohort study.

The prognostic significance of beta(β)-blocker therapy in patients at end-stage renal disease, specifically those receiving peritoneal dialysis (PD) and presenting with heart failure, remains inadequately elucidated due to limited research conducted thus far. A retrospective analysis was performed on a cohort comprising 608 patients receiving PD between September 2007 and March 2019, with a subsequent follow-up period extending until December 2020. Cox regression and propensity score matching weighted analysis was used to model adjusted hazard ratios for β-blocker use with heart failure-related mortality. Competing risk analysis and subgroup analysis were carried out to further elucidate the correlation. β-blockers were prescribed for 56.1% of the peritoneal dialysis patients. Heart failure occurred in 43.4% of the total population and 15.5% of deaths were due to heart failure. The prescription of β-blockers was associated with a 43% lower adjusted hazard ratio (HR) for heart failure death within the cohort (95% confidence interval [CI] = 0.36-0.89; P=0.013). Even after accounting for competing risk events, patients in the group using β-blockers demonstrated a significantly lower cumulative risk of heart failure-related mortality compared to those not using β-blockers (P=0.007). This protective effect of β-blockers was also observed in subgroup analyses. Conversely, β-blocker use had no statistically significant associations with all-cause mortality. The use of β-blockers was associated with a reduced risk of heart failure-related mortality in the PD population. Future randomized clinical trials are warranted to confirm the beneficial effect of β-blockers in the context of PD.

Risks in the Educational Management of Ukraine during War and Post-war Development

Risk management is the main element of the management system in educational institutions. During the war and post-war development, the issue of identifying risks in educational management and assessing their impact on management decision-making takes on from a new perspective. This article analyzes recent studies and publications in the field of risks in educational management, covering both general and those that are specific to the management of educational institutions in tactical, strategic, and post-war horizons. The article also determines risk estimates and presents possible strategies and measures for responding to risk events. The material presented in the article is based on research conducted through interviews with experts. The respondents included middle and senior managers, as well as owners of educational institutions from eight cities and nine regions of Ukraine. In this study, risks were classified by scope and source of occurrence, which were categorized into external and internal risks. Three main groups were identified within external risks: political, economic, and social risks. Internal risks are divided into financial, technical, and managerial risks. A general analysis of expert assessments demonstrated the most and least likely risks and their impact on the management system of world institutions in Ukraine across three time intervals: now, during the war, and post-war reconstruction. Each time dimension is considered in detail, and the change in structure, priority and assessment of the impact of classified risks on the management system of educational institutions is analyzed. For each risk factor, the article provides recommendations on the response strategy and measures to ensure the leveling of the impact of the risk in the management of the educational institution. Special attention is paid to strategies and measures for responding to a risk event in post-war reconstruction, which will make it possible to achieve the set goals in the construction of new directions for the development of Ukrainian educational institutions within the framework of the current Concept of the Strategy of Post-War Reconstruction and Development of Ukraine.

Predicting Highway Risk Event with Trajectory Data: A Joint Approach of Traffic Flow and Vehicle Kinematics

Real-time collision risk prediction is essential for improving highway safety and reducing traffic accidents. However, previous studies have mainly used crash data and associated spatially discrete and temporally continuous traffic data, overlooking the potential of vehicle trajectory data, which provides comprehensive spatio-temporal information to characterize traffic near a specific location. Moreover, researchers have typically focused on either traffic flow characteristics or inter-vehicle microscopic kinematic characteristics for real-time risk prediction, with a dearth of studies integrating these two aspects. Given that risk events transpire more frequently than accidents and exhibit a strong correlation with them, it is imperative to concentrate more on risk events to proactively diminish crash probabilities. This study introduces a novel approach that extracts traffic flow and inter-vehicle kinematic features from risk events. It also provides a comparative analysis of the effectiveness of five machine-learning methods (Logistic Regression, K-Nearest Neighbors, eXtreme Gradient Boosting, Random Forests, and Multilayer Perceptron) and two data-processing strategies (oversampling and undersampling) in addressing risk identification and prediction issues. The results showed that (1) the synergistic use of traffic flow and inter-vehicle kinematic features surpasses the use of a single feature in identifying and predicting risks; (2) The eXtreme Gradient Boosting model, trained on the undersampled dataset, emerges as the optimal model for risk identification, boasting an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.976 and an F1 score of 0.604; (3) The RF model exhibits commendable performance under both risk prediction conditions (5 s ahead prediction and 10 s prediction), demonstrating the highest performance with F1 scores of 0.377 and 0.374, respectively. Additionally, it was discovered that the resampling strategy does not always prove effective in developing risk analysis models and should be chosen based on the model’s characteristics and target metrics. This offers valuable insights into the selection of data-processing strategies when handling unbalanced data. Finally, the study’s limitations and potential enhancements are discussed.

Pre-labor and post-labor cesarean delivery and early childhood adiposity in the Canadian Healthy Infant Longitudinal Development (CHILD) Cohort Study.

Delivery by cesarean section (CS) compared to vaginal delivery has been associated with increased risk of overweight in childhood. Our study examined if the presence or absence of labor events in CS delivery altered risk of overweight in early childhood (1-5 years) compared to vaginal delivery and if this association differed according to infant sex. The study included 3073 mother-infant pairs from the CHILD Cohort Study in Canada. Data from birth records were used to categorize infants as having been vaginally delivered, or delivered by CS, with or without labor events. Age and sex adjusted weight-for-length (WFL) and body mass index (BMI) z scores were calculated from height and weight data from clinic visits at 1, 3 and 5 years and used to classify children as overweight. Associations between delivery mode and child overweight at each timepoint were assessed using regression models, adjusting for relevant confounding factors including maternal pre-pregnancy BMI. Effect modification by infant sex was tested. One in four infants (24.6%) were born by CS delivery; 13.0% involved labor events and 11.6% did not. Infants born by CS without labor had an increased odds of being overweight at age 1 year compared to vaginally delivered infants after adjustment for maternal pre-pregnancy BMI, maternal diabetes, smoking, infant sex and birthweight-for-gestational age (aOR 1.68 [95% CI 1.05-2.67]). These effects did not persist to 3 or 5 years of age and, after stratification by sex, were only seen in boys (aOR at 1 year 2.21 [95% CI 1.26-3.88]). Our findings add to the body of evidence that CS, in particular CS without labor events, may be a risk factor for overweight in early life, and that this association may be sex-specific. These findings could help to identify children at higher risk for developing obesity.

Risk Management Planning by Risk Register in Building Construction Project

This research addresses the common issue of vulnerabilities emerging during construction projects due to inadequate risk identification and analysis. It aims to mitigate this by creating a comprehensive risk register, documenting potential risk events, their causes, and characteristics. The main goal is to identify prominent risk factors in building construction projects and develop a risk management strategy using this register. The study used purposive sampling and considered 22 indicators, including human resources, cost, materials, equipment, and environmental conditions. Questionnaires were distributed to 50 contractors in the Banda Aceh region. Validity and reliability were confirmed through statistical analysis. The analysis showed that human resources were the most prevalent risk factor. Using a probability impact matrix, five indicators had medium-risk levels, while seventeen indicated low risk. Human resources, materials and equipment, and environmental conditions were identified as dominant risk factors, all at a medium-risk level. The study underscores the importance of addressing human resources risks through a structured risk register, which can significantly improve project management and execution. By systematically assessing and mitigating potential risks, project stakeholders can make informed decisions and enhance project outcomes in terms of timelines, costs, and quality. In conclusion, this research highlights the critical role of risk management in construction projects and emphasizes the value of a comprehensive risk register. Addressing dominant risks proactively can positively impact building construction projects.

Supply Chain Risk Management Assessment and Strategy: Case Study in a Hospital Pharmacy

Health service providers such as hospitals have a very diverse supply chain in quantity and type, one of which is medicine. Hospital Pharmacy Installation (IFRS) is one of the health support activity units responsible for planning, procurement, management, storage, distribution, use of drugs, equipment, and pharmaceutical services for medical devices related to the distribution of drugs used in hospitals. Pharmacy has several risks that need to be addressed to increase customer satisfaction. This study aims to determine the extent of the implementation of Supply Chain Risk Management, identify risks in supply chain activities, and obtain risk management strategies. In this study, the method used is the assessment of Supply Chain Risk Management and continued the evaluation of the drug chain in pharmaceutical installations with the House of Risk. It is divided into two stages, namely House of Risk Stage 1, which is used to decide the risk in each supply chain, and House of Risk Stage 2, to offers a decision-making strategy for each chosen decision. There are 20 risk events and 20 risk agents in the House of Risk stage 1, and 11 proposed risk management strategies in the House of Risk stage 2. Out of 20 risks identified in stage 1, 11 risks contributed to 80% highest risk, and the top three are drug shortage, inappropriate planning, and unclear doctor’s writing. In stage 2, the three most prioritized strategies are e-prescription implementation, clear signs for LASA drugs, and conducting supplier performance evaluation.

Mitigation of gayo arabica coffee supply chain risk using the house of risk method in Aceh Tengah

Aceh Tengah District is the largest Gayo Arabica Coffee production area in Aceh Province. Therefore, coffee has an important role in the economy of the people of Aceh Tengah, both as a source of income for coffee farmers, a source of foreign exchange and as a provider of employment through processing, marketing and trading activities. However, Gayo Arabica Coffee farmers are often faced with many obstacles and risks in run their business. The aim of this research is to analyze the risks with the highest impact on the Gayo Arabica Coffee supply chain and formulate mitigation to reduce the risk impact on it by using the House of Risk (HOR) method. Based on the research results, 42 risk events and 37 risk agents were obtained and 7 dominant risk agents were obtained which could be prevented with 9 mitigation strategies. The risk with the highest impact on the Gayo Arabica Coffee supply chain in Aceh Tengah District is assessed based on the highest to lowest Aggregate Risk Potential (ARP) value using the 67:20 Pareto Diagram. Mitigation strategies for Gayo Arabica Coffee supply chain risks in Aceh Tengah District are assessed based on the Effectiveness to Difficulty (ETD) value from highest to lowest.

DETERMINANTS OF PREGNANCY LOSS AMONG WOMEN OF REPRODUCTIVE AGE IN INDONESIA

Background. Both miscarriage and stillbirth occur in almost 20% of clinical pregnancies, resulting in pregnancy loss. The incidence has been associated with several risk factors and events of maternal adverse health outcomes. Purpose. This study was conducted to analyze some associated factors of pregnancy loss in Indonesia. Methods. This cross-sectional study used the 2017 Indonesia DHS data involving 18,882 female participants aged 15–49 years who had ever had a gestation. Pregnancy loss was the dependent variable, whereas the independent variables included education, employment, wealth status, advanced maternal age, grand multiparity, and cigarette smokers. Finally, the author used binary logistic regression to calculate the determinants. Results. The adjusted risk of pregnancy loss was significantly higher in respondents with lower education levels (AOR=1.25; 95% CI: 1.11-1.41) and employed (AOR=1.19; 95% CI: 1.10-1.29). The lower the wealth status of women, the higher the chance of pregnancy loss. The adjusted risk of pregnancy loss was higher in women of advanced maternal age (AOR=2.03; 95% CI: 1.37-3.02), those with grand multiparity (AOR=1.91; 95% CI: 1.74-2.09), and those who cigarette smokers (AOR=1.53; 95% CI: 1.25-1.87). Conclusion. The study concluded that six variables i.e., education, employment, wealth status, advanced maternal age, grand multiparity, and cigarette smokers are strong predictors of pregnancy loss in Indonesian women. Therefore, the government should make a policy to address the determinants of the pregnancy issue.