Search Results (229)

Background: Prostate cancer is the fourth most common cancer and eighth leading cause of cancer-related mortality worldwide. Its incidence is increasing in South Korea. This study aimed to investigate a predictive model for the 5-year survival probability of prostate cancer patients in a Korean primary care setting. Method: This retrospective study used data from the nationwide insurance claims database. The main outcome was survival probability 5 years after the initial diagnosis of prostate cancer. Potential confounding factors such as age, body mass index (BMI), blood pressure, laboratory results, lifestyle behaviors, household income, and comorbidity index were considered. These variables were available in the national health check-up information. A Cox proportional hazards regression model was used to develop the predictive model. The predictive performance was calculated based on the mean area under the receiver operating characteristic curve (AUC) after 10-fold cross-validation. Results: The mean 5-year survival probability was 82.0%. Age, fasting glucose and gamma-glutamyl transferase levels, current smoking, and multiple comorbidities were positively associated with mortality, whereas BMI, alkaline phosphatase levels, total cholesterol levels, alcohol intake, physical activity, and household income were inversely associated with mortality. The mean AUC after 10-fold cross-validation was 0.71. Conclusions: The 5-year survival probability model showed a moderately good predictive performance. This may be useful in predicting the survival probability of prostate cancer patients in primary care settings. When interpreting these results, potential limitations, such as selection or healthy user biases, should be considered. Full article

This paper analyzes the factors influencing households’ resilience capacities to shocks within Kenya’s fisheries and aquaculture sectors and draws from primary data collected from 419 fish-dependent households across Kisumu, Busia, Mombasa, and Kilifi counties. The sample represents a total of 48,000 fishing households. The study adopted a quasi-longitudinal design and computed the household resilience capacity index (RCI) using the resilience index measurement and analysis (RIMA-II) model. The results indicate that male-headed households’ mean household RCI scores (mean = 45.07 ± 10.43) were statistically significant to that of female-headed households (mean = 38.15 ± 9.25), suggesting that female-headed households are associated with lower resilience capacities than male-headed households. Moreover, the study identifies differences in resilience levels across various occupations within the sector. For instance, RCI scores among fish traders (mean = 40.71 ± 9.97), a function performed mainly by women, statistically differed (p < 0.005) from male-dominated cage farming (mean = 48.60 ± 10.47), whereas RCI scores at the production level for fisher folks (mean = 44.89 ± 10.09) and pond farmers (mean = 44.04 ± 12.07) showed no statistical difference (0 > 0.05. Additionally, households with more income sources tend to have higher resilience capacities. Seasonality in fishing cycles limited households’ ability to recover from climate-induced shocks; the more months without fishing activity, the less the odds of recovery from shocks (OR = 0.532, 95% CI [0.163, 0.908], p = 0.022). Furthermore, households that lacked guaranteed market access and inputs during COVID-19 were less likely to recover during and after the shocks (OR = 0.401, 95% CI [0.161, 0.999], p = 0.05). Households organized in cooperatives with better access to credit showed a higher chance of recovery. The study recommends (a) adopting gender-sensitive approaches in fisheries and aquaculture interventions to empower women in trade, (b) strengthening policies to enhance access and adoption of climate-smart technologies such as cage fish farming, (c) promoting livelihood diversification to sustain households’ income during fishing off-seasons, and (d) enhancing market linkages in the fish value chain through coordinated producer organizations. Further research should explore the possibilities of introducing index-based weather insurance and other tested suitable safety nets for the fisheries and aquaculture sector. Full article

Index-based insurance is an innovative concept for evaluating agricultural risks and payouts, which uses an index instead of traditional on-site loss assessment. Area yield insurance, as an index-based approach, is an effective strategy to mitigate moral hazard and adverse selection issues. This study aims to develop area yield insurance as a new insurance plan in Iran for two major crops: wheat and barley. It utilized kernel and joint kernel distributions to price the insurance and assessed producer welfare benefits by comparing the certainty equivalence (CE) of farmers’ utility with and without the policy. Data were collected from East Azerbaijan Province, including county-level yield data for irrigated and rainfed wheat and barley from 1975 to 2019 and 446 individual-level yield data from 2015 to 2019. A two-stage method was used to model yield risk: the first stage fits a trend model, while the second estimates the yield distributions with the detrended data. The results showed a significant difference in premiums calculated by the two distributions, with joint kernel distribution offering the best empirical fit and reasonable premiums. The findings indicate that area yield crop insurance provides positive welfare benefits and should serve as a viable alternative or complement to existing yield insurance plans. The successful implementation of this policy in various countries suggests it can be a suitable risk management program for developing countries like Iran. Full article

Background: The overall survival rates among cancer patients have been improving. However, the increase in survival is not uniform across socioeconomic status. Thus, we investigated income disparities in the 5-year survival rate (5YSR) in cancer patients and the temporal trends. Methods: This study used a national cancer cohort from 2002 to 2018 that was established by linking the Korea Central Cancer Registry and the National Health Insurance Service (NHIS) claim database to calculate the cancer survival rate by income level in the Republic of Korea. Survival data were available from 2002 onward, and the analysis was based on the actuarial method. We compared the survival of the earliest available 5-year period of 2002–2006 and the latest available 5-year period of 2014–2018, observing until 31 December 2021. Income level was classified into six categories: Medical Aid beneficiaries and five NHIS subtypes according to insurance premium. The slope index of inequality (SII) and relative index of inequality were used to measure absolute and relative differences in 5YSR by income, respectively. Results: The 5YSR between the 2002–2006 and 2014–2018 periods for all cancers improved. A significant improvement in 5-year survival rates (5YSR) over the study period was observed in lung, liver, and stomach cancer. The SII of survival rates for lung (17.5, 95% confidence interval (CI) 7.0–28.1), liver (15.1, 95% CI 10.9–19.2), stomach (13.9, 95% CI 3.2–24.7), colorectal (11.4, 95% CI 0.9–22.0), and prostate (10.7, 95% CI 2.5–18.8) cancer was significantly higher, implying higher survival rates as income levels increased. The SII for lung, liver, and stomach cancer increased, while that of thyroid, breast, cervical, prostate, and colorectal cancer decreased over the study period. Conclusions: Although substantial improvement in the 5YSR was observed across cancer types and income levels from 2002 to 2018, this increase was not uniformly distributed across income levels. Our study revealed persistent income disparities in the survival of cancer patients, particularly for lung and liver cancer. Full article

Introduction: Obesity, in addition to many other negative health consequences, affects pulmonary function and is a potential risk factor for asthma. Methods: We analyzed the association of body mass index (BMI) with incident asthma among 60,639 Finnish men and women aged 25 to 74 years who participated in a population-based chronic disease risk factor survey in 1972, 1977, 1982, 1987, 1992, 1997, 2002, 2007, or 2012. Data on lifestyle factors such as smoking and physical activity, as well as medical history, were obtained, and various physical measurements, including height and weight, were taken at baseline. Incident asthma events were ascertained from the National Social Insurance Institution’s register data. The study cohorts were followed-up until the end of 2017 through registers. Results: During the follow-up, 4612 (14%) women and 2578 (9.3%) men developed asthma. The risk of asthma was analyzed in the following three BMI categories: <24.9 (reference category), 25–29.9 (overweight) and ≥30 kg/m² (obesity). Hazard ratios (95% CI) were 1.34 (1.24–1.43) and 1.57 (1.44–1.71) in women and 1.25 (1.14–1.37) and 1.63 (1.44–1.83) in men. The observed association was independent of smoking, height and leisure-time physical activity. In women, 30.8% (19.2% in men) of the total asthma incidence was attributed to overweight and obesity. Conclusions: Overweight and obesity are important risk factors for asthma. Full article

Background and Objectives: Although statins are recommended for secondary prevention of acute ischemic stroke, some population-based studies and clinical evidence suggest that they might be used with an increased risk of intracranial hemorrhage. In this nested case–control study, we used Taiwan’s nationwide universal health insurance database to investigate the possible association between statin therapy prescribed to acute ischemic stroke patients and their risk of subsequent intracerebral hemorrhage and all-cause mortality in Taiwan. Materials and Methods: All data were retrospectively obtained from Taiwan’s National Health Insurance Research Database. Acute ischemic stroke patients were divided into a cohort receiving statin pharmacotherapy and a control cohort not receiving statin pharmacotherapy. A 1:1 matching for age, gender, and index day, and propensity score matching was conducted, producing 39,366 cases and 39,366 controls. The primary outcomes were long-term subsequent intracerebral hemorrhage and all-cause mortality. The competing risk between subsequent intracerebral hemorrhage and all-cause mortality was estimated using the Fine and Gray regression hazards model. Results: Patients receiving statin pharmacotherapy after an acute ischemic stroke had a significantly lower risk of subsequent intracerebral hemorrhage (p < 0.0001) and lower all-cause mortality rates (p < 0.0001). Low, moderate, and high dosages of statin were associated with significantly decreased risks for subsequent intracerebral hemorrhage (adjusted sHRs 0.82, 0.74, 0.53) and all-cause mortality (adjusted sHRs 0.75, 0.74, 0.74), respectively. Conclusions: Statin pharmacotherapy was found to safely and effectively reduce the risk of subsequent intracerebral hemorrhage and all-cause mortality in acute ischemic stroke patients in Taiwan. Full article

Index insurance for forage, pasture, and rangeland has gained ground in policy and academic circles. Stakeholders promote it as an innovative risk management tool for enhancing resilience to drought-induced perils and providing a way for consumption smoothing to livestock producers in drought vulnerable ecosystems. Index insurance, which avoids market failures such as moral hazard, adverse selection, and transactional cost, has been piloted and implemented all over the world. To support future development and research on index-based insurance in livestock systems, operational index insurance for forage, pasture, and rangeland systems in developed (USA and Canada) and developing (Kenya and Ethiopia) countries are reviewed and compared. This paper finds some similar characteristics (huge subsidy payments—ranging from 50 to 100 percent, significant government role, low adoption, insufficient payouts, data challenges, etc.), of this product between the two regions. A major difference between the PRF and NDVI is the number of choices available to users of rainfall index insurance who face close to 3000 choice options, while NDVI users have less than 5 choice options available for them. Based on these insights, we highlight opportunities where the two regions can benchmark and improve upon their respective index insurance schemes—index-based livestock insurance (IBLI) in developing and rainfall index insurance for forage in developed regions. Full article

Innovations are vital for empowering women and youth by introducing alternative pathways for development. This study focuses on a social innovation project executed in Dasenech, South Omo, Ethiopia. The project introduced innovative initiatives (index-based livestock insurance (IBLI), a goat market value-chain system, an eco-friendly hydraulic ram pump, fodder production, and a vet drug store). Key among the goals of these initiatives was the empowerment of pastoralist women by promoting the livelihood base of the Dasenech Pastoralist Community. The present study assessed the contributions of these innovations to the empowerment of women and youth. We employed a mixed-method research approach to pool both quantitative and qualitative data using a household survey through Kobocollect, FGDs, KIIs, and case stories. We computed empowerment by employing a 5DE model with five domains, i.e., production, resources, income, leadership, and time use. The findings suggest that 93% of the project participants were empowered, recording “adequate achievements” in line with the 5DE model, i.e., with scores of at least 80% in four of the five requirements. Technological innovations that properly assess the context of the intervention area and, most importantly, that use proper avenues of implementation with women and youth as owners and leaders, have the capacity to empower such individuals in the economic, social, and political spheres. Full article

We construct a model where, at each time instance, risky securities can only take a limited number of values and the equity-linked policy sold by the insurer to policyholders pays benefits linked to these securities. Since the number of states in the model exceeds the number of securities in the (incomplete) market, the martingale measure is not unique, posing a problem in pricing insurance instruments. In this framework, we consider how a super-replicating strategy violates the assumption of absence of arbitrage, yet simultaneously allows the insurance company to fully hedge against financial risk. Since the super-replicating strategy, when considered alone, would be too costly for any rational insured person, through the definition of the safety loading, we demonstrate how the insurer can still hedge against financial risk, albeit at the expense of increasing its exposure to demographic risk. This approach does not aim to show how the pricing of the index-linked policy can actually be performed but rather highlights how risk theory-based approaches (via the definition of the profit and loss random variable) enable the management of the trade-off between financial risk and demographic risk. Full article

Background: The global rise of obesity and its association with cardiovascular risk factors (CVRF) have highlighted its connection to chronic heart failure (CHF). Paradoxically, obese CHF patients often experience better outcomes, a phenomenon known as the ‘obesity paradox’. This study evaluated the ‘obesity paradox’ within a large cohort in Germany and explored how varying degrees of obesity affect HF outcome. Methods: Anonymized health claims data from the largest German insurer (AOK) for the years 2014–2015 were utilized to analyze 88,247 patients hospitalized for myocardial infarction. This analysis encompassed baseline characteristics, comorbidities, interventions, complications, and long-term outcomes, including overall survival, freedom from CHF, and CHF-related rehospitalization. Patients were categorized based on body mass index. Results: Obese patients encompassed 21.3% of our cohort (median age 68.69 years); they exhibited a higher prevalence of CVRF (p < 0.001) and comorbidities than non-obese patients (median age 70.69 years). Short-term outcomes revealed lower complication rates and mortality (p < 0.001) in obese compared to non-obese patients. Kaplan–Meier estimations for long-term analysis illustrated increased incidences of CHF and rehospitalization rates among the obese, yet with lower overall mortality. Multivariable Cox regression analysis indicated that obese individuals faced a higher risk of developing CHF and being rehospitalized due to CHF but demonstrated better overall survival for those classified as having low-level obesity (p < 0.001). Conclusions: This study underscores favorable short-term outcomes among obese individuals. The ‘obesity paradox’ was confirmed, with more frequent CHF cases and rehospitalizations in the long term, alongside better overall survival for certain degrees of obesity. Full article

The analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to predict the mortality of two or more related populations simultaneously are particularly important. Indeed, these models, in addition to improving the forecasting accuracy overall, enable evaluation of the basis risk in index-based longevity risk transfer deals. This paper implements and compares several model-averaging approaches in a two-population context. These approaches generate predictions for life expectancy and the Gini index by averaging the forecasts obtained using a set of two-population models. In order to evaluate the eventual gain of model-averaging approaches for mortality forecasting, we quantitatively compare their performance to that of the individual two-population models using a large sample of different countries and periods. The results show that, overall, model-averaging approaches are superior both in terms of mean absolute forecasting error and interval forecast accuracy. Full article

This is a study of decision problems under two-dimensional risk. We use an existing index of absolute correlation aversion to conveniently classify bivariate preferences, with respect to attitudes toward this risk. This classification seems to be more important than whether decision makers are correlation-averse or correlation-seeking for the study of insurance demand when a loss has a multidimensional impact. On this note, we also re-examine Mossin’s theorem under bivariate preferences, where full insurance is preferred with a fair premium, while less than full coverage is preferred with a proportional premium loading. Furthermore, based on the comparative statics of this two-dimensional insurance model for changes in correlation aversion, we derive testable implications about the classification of bivariate utility functions. For the particular case when the two-dimensional risk can be interpreted as risk on income and health, we identify the form of separable utility functions depending on health status and income that is consistent with household disability insurance decisions. Full article

Systemic risk refers to the potential for a disruption in one part of a financial system to trigger a cascade of adverse effects, impacting the functioning of the system. Despite the progress on novel systemic risk measures, research on dynamics of systemic risk network structure and its community effect is still in its initial state. In this study, we utilize price data from 107 representative Chinese stocks spanning the period from 2017 to 2022. A systemic risk network is derived from the Risk Transmission Index based on TENET and the QR–Lasso model. By utilizing DBSCAN, HITS and community detection algorithms on the network, we aim to propose a more suitable definition of systemically important companies, explore the interrelationships between companies, and discuss its plausible reasons for dynamics structural changes. The empirical findings demonstrate a substantial involvement of insurance companies in both contributing to and receiving systemic risk within the analyzed context. We identify prominent risk output and input centers, and emphasize the profound impact of the COVID-19 pandemic on the dynamics of systemic risk. Full article

Background: Insulin resistance (IR) is assessed using surrogate markers such as the triglyceride–glucose (TyG) index, the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and the metabolic score for IR (METS-IR). Limited studies investigated their association with colorectal cancer (CRC) incidence, and no research has been conducted on their association with the METS-IR. Method: This study used claims data from the Korean National Health Insurance Service, analyzing a cohort of 314,141 Koreans aged over 40 who participated in the National Health Screening Program from 2009 to 2010. The follow-up period was extended until 31 December 2019. Participants were divided into four groups based on quartiles (Q1–Q4) of the markers. Results: All surrogate markers of IR had sequentially statistically lower disease-free probabilities from Q1 to Q4. The Cox proportional hazard model demonstrated statistically significant positive associations between CRC incidence and Q3 and Q4 of the TyG index, as well as Q3 and Q4 of the TG/HDL-C ratio and Q4 of the METS-IR. The constrained cubic spline method revealed a nonlinear, positive dose–response relationship between the TyG index and the METS-IR in relation to CRC incidence. Conclusions: In conclusion, the TyG index, TG/HDL-C ratio, and METS-IR were positively correlated with CRC incidence in Koreans. Full article

Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and handling complex data by adjusting the complexity of the model through the addition or reduction of terms. Moreover, quantile generalized additive regression was deliberated to evaluate relationships with lower quantiles, such as low-yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as conditional tail expectation (CTE), certainty equivalence of revenue (CER), and mean root square loss (MRSL). The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R² of 0.691. MRSL should be taken into consideration initially, as it is a farmer’s revenue assessment that distinguishes between those with and those without insurance. As a result, the GAM model indicates the least fluctuation in farmer income at the 90th percentile. Additionally, our study suggests that this type of insurance could apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production. Full article