Bivariate Model Research Articles

Association of Exposure to Interpersonal Racism and Racial Disparities in Inadequate Sleep Risk

To examine the association between caregiver-report of their child's inadequate sleep and exposure to interpersonal racism within racially minoritized subpopulations. We conducted cross-sectional analysis among racially minoritized 21,924 school-aged children and 27,142 adolescents using a National Survey of Children's Health (NSCH) sample from 2016 through 2021. Multivariable logistic regression models were fit to estimate predicted probabilities for the adjusted associations between caregiver-report of their child's inadequate sleep and prior exposure to interpersonal racism. In bivariate models, caregiver report of child exposure to interpersonal racism was significantly associated with a higher probability of inadequate sleep within non-Hispanic Asian American/Pacific Islander (AAPI) school-aged children, Hispanic adolescents, and non-Hispanic multiracial adolescents. After adjusting for covariates, only the association within Hispanic youth remained significant though attenuated. Unexpectedly, non-Hispanic Black school-age children exposed to racism had a lower probability of inadequate sleep than non-Hispanic Black children without exposure to racism after adjusting for covariates. Nationally representative pooled data that showed caregiver-report of Hispanic adolescents' inadequate sleep was associated with their exposure to interpersonal racism, although an association with inadequate sleep was not found in other racially minoritized subpopulations. Examining within-race associations helps to assess more accurately risk and target efforts that seek to address racism-related stress among racially minoritized subpopulations.

Landslide susceptibility assessment along highways (SH-12 and NH-717A) in Darjeeling Himalayas

Landslides are the utmost damaging natural along with anthropogenic hazards which cause huge damage to assets and human lives in hilly environments all over the world. The key aim of this study is to explore landslide susceptibility (LS) maps along highways (SH-12 and NH-717A) in the Darjeeling Himalayas, India. Four data-driven bivariate statistical models (BSMs) were used to develop LS maps based on geospatial techniques. A total of 90 (100%) polygons with different size of landslide locations were identified to develop landslide inventory/distribution (LI/LD) map by incorporating Google Earth and satellite imageries, and filed investigation through the global positioning system (GPS). The LI/LD map is distributed into testing 30% (27 landslide locations), and training 70% (63 landslide locations) of the models. Eighteen landslide causative factors (LCFs) were selected to develop LS maps. Multicollinearity analysis showed that there is no collinearity problem in the LCFs. The receiver operating characteristics (ROC) curve and frequency ratio (FR) value techniques were applied for validation. The relative importance of each LCF for each model has been measured using Jack-knife test. The LS maps were divided into six landslide susceptibility zones (LSZs). The ROC curve showed the accuracy of the LSZ maps is 93.50% for FR, 85.90% for evidential belief functions (EBFs), 81.80% for fuzzy membership (FM) using FR, and 77.20% for FM using cosine amplitude (CA) approaches respectively. Among all models, the FR model showed the highest percentage of accuracy for LS assessment and prediction. The FR values of six LSZs rise from very low to very high LSZs which indicate a positive correlation between LSZs and FR values. The results of Jack-knife test showed that terrain ruggedness index (TRI) factor has the highest relative importance for all models in LSZ mappings. The study findings will help to the planner, and policymakers for spatial planning, implement slope management strategies, land use management in mountainous environments.

Evaluating Bias of Child Maltreatment Referrals in Encounters for Unintentional Ingestions

BackgroundUnintentional ingestions commonly result in presentation to the pediatric emergency department (PED). No standardized recommendations exist regarding when to call Child Protective Services (CPS) for unintentional ingestions, which allows for the possibility of biased decision-making. ObjectiveIdentify patient and visit level characteristics associated with CPS referral status in unintentional ingestion encounters. Participantsand Setting: Retrospective cross-sectional study of children ≤6 years old presenting with unintentional ingestion to a metropolitan PED from 2015 to 2021. MethodsICD-10-CM codes were used to identify unintentional ingestion visits in the electronic health record. CPS referral was determined by manual chart review. Bivariable and multivariable logistic regression models identified patient and visit level characteristics associated with CPS referral. Socioeconomic status (SES) was classified based on zip code, the Child Opportunity Index data, and insurance. ResultsOf 3,836 charts reviewed, 808 met inclusion criteria. CPS referrals were made in 109 (13.5%) visits. Compared to non-Hispanic white patients, non-Hispanic Black patients had 7.37 (95% CI:1.38, 39.26) higher adjusted odds of being referred to CPS after adjusting for triage level, age, and ingestion type. Patients in the Lowest SES group had a 3.01 (95% CI:1.42, 6.40) higher adjusted odds when compared to the Middle/Highest SES group. ConclusionThis study found that CPS referrals in unintentional ingestions occur more often in those identifying as non-Hispanic Black and in those in the Lowest SES group, suggesting clinician bias may impact the decision regarding referrals. To mitigate subjective decision-making, we propose creating standardized, objective CPS referral criteria for unintentional ingestions.

Evolution of Pancreas Transplantation At A Single Institution-50+ Years and 2500 Transplants.

To describe the evolution of pancreas transplantation, including improved outcomes and factors associated with improved outcomes over the past 5 decades. The world's first successful pancreas transplant was performed in December 1966 at the University of Minnesota. As new modalities for diabetes treatment mature, we must carefully assess the current state of pancreas transplantation to determine its ongoing role in patient care. A single-center retrospective review of 2500 pancreas transplants was performed over >50 years in bivariate and multivariable models. Transplants were divided into 6 eras; outcomes are presented for the entire cohort and by era. All measures of patient and graft survival improved progressively through the 6 transplant eras. The overall death-censored pancreas graft half-lives were >35 years for simultaneous pancreas and kidney (SPK), 7.1 years for pancreas after kidney (PAK), and 3.3 years for pancreas transplants alone (PTA). The 10-year death-censored pancreas graft survival rate in the most recent era was 86.9% for SPK recipients, 58.2% for PAK recipients, and 47.6% for PTA. Overall, graft loss was most influenced by patient survival in SPK transplants, whereas graft loss in PAK and PTA recipients was more often due to graft failures. Predictors of improved pancreas graft survival were primary transplants, bladder drainage of exocrine secretions, younger donor age, and shorter preservation time. Pancreas outcomes have significantly improved over time through sequential, but overlapping, advances in surgical technique, immunosuppressive protocols, reduced preservation time, and the more recent reduction of immune-mediated graft loss.

Bivariate cubic normal distribution for non-Gaussian problems

Probabilistic models play critical role in various engineering fields. Numerous critical issues exist in probabilistic modeling, especially for non-Gaussian correlated random variables. However, conventional parameter-based bivariate distribution models are generally developed for specific types of random variables, limiting their flexibility and applicability. A flexible bivariate distribution model is proposed, in which the joint cumulative distribution function is derived with the probability equivalently expressed as the summation of three basic probabilities corresponding to simple functions. These three basic probabilities are calculated with the aid of univariate cubic normal distribution, and thus the proposed model is named as bivariate cubic normal (BCN) distribution. The proposed BCN distribution has been applied in modeling several common bivariate distributions and actual engineering datasets. Results show that the BCN model accurately models both typical theoretical distributions and the JCDF of practical datasets, offering a significant improvement over existing models. Furthermore, the proposed BCN distribution has been utilized in seismic reliability assessment and the calculation of the mean recurrence interval and hazard curve of hurricane wind speed and storm size. Results demonstrate that the BCN distribution excels in modeling and matching capabilities, proving its accuracy and effectiveness in civil engineering applications.

Level of option B+PMTCT drug adherence with male partner involvement and associated factors among breastfeeding women until 18 months in North Gojjam Zone, Amhara region, Northwest Ethiopia, 2022: a multicentre cross-sectional study

BackgroundAdherence to option B+antiretroviral therapy medication is crucial for the effective implementation of the Prevention of Mother-to-Child Transmission (PMTCT) programme. Ethiopia has adopted the WHO’s target of achieving over 95%...

A probabilistic framework for offshore aquaculture suitability assessment using bivariate copulas

Aquaculture at sea is gaining increasing importance, not only as a (local) food source but also due to its potential of being combined with other offshore activities such as wind parks. Nevertheless, experience of offshore aquaculture is limited. This study aims to provide a framework to evaluate offshore aquaculture suitability accounting for the probabilistic dependence between relevant variables. This framework is applied to obtain suitability maps of aquaculture for the North Sea for the blue mussel Mytilus edulis and the sugar kelp Saccharina latissima. For each of these species, three ecological variables are selected and the optimal growth and critical survival limits are defined. Here, suitability is defined as the probability of meeting these conditions. Data on the selected variables is extracted from a large-scale 3D hydrodynamic and ecological model of the northwest European Shelf, of which daily extremes are sampled. The probabilistic model is developed using bivariate copula models, which are fitted to each variable pair to describe their joint distribution function at each studied location. Empirical distribution functions are used to describe the univariate distribution function of each variable and location. Using Monte-Carlo simulations, the probability of meeting the optimal and critical limits is estimated and suitability maps accounting for the probabilistic dependence between the variables are generated. In addition, suitability maps disregarding the dependence are generated and compared to those accounting for the probabilistic dependence. It was found that considering the dependence between variables significantly improves the accuracy of the results for optimal and critical growth conditions for both species. The presented method allows to identify potential areas where blue mussel and sugar kelp cultivation is the most suitable. For instance, in this study, a north-south elongated area west of the German and Danish coast appears to be most suitable for blue mussels, while estuaries and rivers are found the most suitable for the sugar kelp.

Enhancing Drought Risk Assessment in the Punjab, Pakistan: A Copula-Based Modeling Approach for Future Projections

Abstract Drought is one of the most complicated and challenging natural hazards, which occurs nearly in every part of the world and poses recurring challenges to agriculture, food security, livestock, human health, and water management. Pakistan has a long history of drought; however, this study focuses on drought analysis and projection in the province of Punjab, Pakistan, as it provides around 60% of the country’s food product, significantly contributing to the national food supply and economy. This study utilized the previous 56 years (1962–2017) of climate data to calculate the reconnaissance drought index (RDI) and then extracted the drought variables of durations and severity for each meteorological station. The best-fit marginal probability distribution and copula models were chosen for the stations based on numerical as well as graphical evaluation. Lognormal and exponential probability distributions, as well as Gumbel, are selected as the best-fit probability distributions for both drought characteristics and bivariate copula model, respectively, for projections. From the projections, we can infer that the smaller return periods indicate high vulnerability while longer return periods with low vulnerability. The results suggest that Faisalabad, Bahawalpur, Bahawalnagar, and Multan stations have the lowest return periods, indicating high vulnerability, and may experience drought more frequently in the future. Mianwali, Khanpur, Lahore, and Sialkot stations may have an intermediate vulnerability to drought events. The stations of Jhelum, Murree, and Sargodha have larger return periods, implying lower susceptibility to drought events in the future. The projected results provide insights for policymakers and stakeholders to optimize the risk of droughts on agriculture production, livestock, water management, human health, and food security in Punjab, Pakistan.

Reciprocal regulation between rural settlement expansion and human-elephant conflict in China's wild elephant range

Human-wildlife conflict (HWC) and its socioeconomic impacts are a pressing global issue. Accurately quantifying HWCs and their interaction with residential development is crucial for rural revitalization and biodiversity conservation efforts. This study investigates the interplay between rural residential expansion (RRE) with human-elephant conflict (HEC) in southern Yunnan Province using high-accuracy yearly land use/land cover data and Asian elephant accident data. A piecewise regression along with several metrics, including expansion intensity and rate of rural residential land, and residential density, were employed to analyze the spatial-temporal change characteristics of RRE. Then, a geographical detector and a bivariate spatial autocorrelation model were used to reveal the driving mechanisms of RRE, with particular emphasis on the spatial relations between RRE and HECs. The results indicate that HECs had a significant negative impact on RRE, exhibiting higher expansion intensity and rate of rural residential land in non-HEC areas than in HEC areas. High spatiotemporal consistency between accelerated RRE and intensified HECs occurred from 2010 onwards, which aligns with the year when the trend of settlement area expansion changed. RRE activities and ensuing land use conversions led to increased occurrences of HECs, which negatively affected the RRE. Compared to HECs, topography and locational factors exhibited a secondary effect on RRE activities. The findings underscore reciprocal feedback mechanisms between RRE and HECs and the elevated risk of adverse interactions between humans and elephants within the range of China's wild elephants, providing theoretical support for coordinating conservation initiatives for Asian elephants with rural revitalization in the border areas of Southwest China.

Women's satisfaction with comprehensive abortion care services and associated factors in central Gondar zone public primary hospitals, northwest Ethiopia, 2023.

Abortion complications are the leading causes of maternal death in low and middle-income countries, including Ethiopia. Providing quality and comprehensive abortion care services is crucial for improving the health of women and increased their satisfaction. Evaluating a client's satisfaction with abortion care is clinically relevant since women's satisfaction with health services is one of the key indicators of high-quality healthcare services. Therefore, this study aimed to assess women's satisfaction with comprehensive abortion care services and associated factors. An institution-based cross-sectional study was implemented among 333 women in Central Gondar Zone public primary hospitals from October 1, 2022, to April 30, 2023. Eligible participants were selected using a systematic random sampling technique. The data was collected using an interviewer-administered semi-structured, and pretested questionnaire. STATA version 17 and SPSS version 25 software were used for data entry and analysis respectively. Bivariable and multivariable logistic regression models were used to identify factors associated with clients' satisfaction with comprehensive abortion care services. A P-value of ≤0.05 with a 95% confidence interval was the cutoff point for determining statistical significance. This study revealed that the level of client satisfaction with comprehensive abortion care services was 60.4% (95% CI: 55.0%, 66.0%). The use of abortion medication (AOR = 4.41, 95% CI: 2.59, 7.48), women's age 20-24 years (AOR = 2.94, 95% CI: 1.02, 8.48), and being a student (AOR = 2.88, 95% CI: 1.10, 7.51) were significantly associated with women's satisfaction with comprehensive abortion care services. Women's satisfaction with comprehensive abortion care services was relatively low, and it was strongly correlated with the method of abortion, age, and occupation. To improve women's satisfaction requires a comprehensive understanding of women's values and perspectives, providing sexual and reproductive health education, and quality abortion care services are recommended.

A study on the genetic and phenotypic factors affecting specific ewe productivity traits in Sangsari sheep.

The study's objectives were to assess the genetic parameters of reproductive characteristics in Sangsari sheep. A data set of reproductive information with pedigree details from 1995 to 2016 was used. Studied traits were litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB) and total litter weight at weaning (TLWW). Test significance of the environmental factors to be included in the model was conducted using the general linear model procedure of the SAS program. All traits were significantly affected by the year of lambing and ewe age at lambing (P < 0.01). The AI-REML procedure of the Wombat program was used to evaluate genetic parameters. A series of bivariate animal models were employed to calculate genetic (rg) and phenotypic (rp) correlations between traits. The total least square means ± standard error of LSB and LSW were 1.04 ± 0.05 and 0.96 ± 0.03, while LMWLB, LMWLW, TLWB, and TLWW were 3.12 ± 0.08, 15.40 ± 0.13, 3.28 ± 0.04, and 19.31 ± 0.16kg, respectively. The estimates of h2 were relatively low (P < 0.01) and ranged from 0.063 ± 0.028 for LSW to 0.181 ± 0.063 for TLWW. Repeatability estimates varied from 0.101 for LSW to 0.241 for TLWW. The sire service effects for LMWLB, TLWB, and TLWW were 0.012 ± 0.004, 0.023 ± 0.006, and 0.039 ± 0.009, respectively. The traits studied showed a greater magnitude of genetic correlation than phenotypic correlation, with values ranging from - 0.59 (LSB-LMWLB) to 0.87 (LMWLB-TLWB). It appears that focusing on TLWW for selection could result in more significant improvements in the reproductive performance of Sangsari ewes.

Financial needs and opioid use among head and neck cancer (HNC) survivors: Baseline findings from the HN-STAR trial (WF-1805CD).

365 Background: HNC survivors often experience post-treatment pain. Given known disparities in pain management and opioid use in the non-cancer population, we explored sociodemographic predictors of opioid use in HNC survivors enrolled in the HN-STAR trial (NCT04208490, funding: American Cancer Society and UG1CA189824). Methods: Survivors of HNC (stages I-III) who completed therapy 6-24 months prior and had no evidence of disease were enrolled throughout the NCI Community Oncology Research Program (NCORP). Survivors were randomized to a clinical informatics intervention or usual care. Baseline surveys elicited recent prescription opioid use in the prior week (yes/no). Blinded to arm assignment, we conducted bivariate analyses of recent opioid use and the following sociodemographic predictors: age, gender, marital status, race and ethnicity (non-white/Latinx vs all others), highest level of education, and being able to meet daily financial needs in the prior 4 weeks. We conducted stepwise multivariable logistic regression to evaluate the association of these factors on opioid use. Results: Among 254 survivors (mean age 63, 74% male, 25% non-white/non-Latinx, 13% reporting financial need) at 25 oncology practices, 14% (n=35) reported recent opioid use. In bivariate analyses, survivors who reported financial needs were more likely to have used opioids (odds ratio [OR] 4.35, 95% confidence interval [CI] 1.85-10.20, p&lt;.001). In stepwise multivariable analyses, only having financial needs remained in the final model (Table). Conclusions: In a national sample of post-treatment HNC survivors during a subacute survivorship period (6-24 months after treatment completion), 1 in 7 survivors reported using opioids in the past week – more than twice the annual rate of opioid receipt in the general adult population. Several demographic factors related to opioid use were examined and not associated with recent opioid use among HNC survivors. Findings suggest that financial concerns may be a barrier to non-narcotic pain management (e.g., cognitive behavioral approaches, physical therapy) – or simply that unmet financial needs are associated with lower quality of pain management. Attention should focus on equitable pain management in this population. Clinical trial information: NCT04208490 . Predictors of opioid use in past week. Bivariate Models Estimate (standard error) p-value Age (years) -.01 (.02) .52 OR (95% CI) p-value Female .98 (.41, 2.16) .97 Latinx/non-white .71 (.27, 1.63) .45 Married .56 (.27, 1.18) .13 Some college or more .62 (.30, 1.30) .20 Had financial needs 4.35 (1.85,10.20) &lt;.001 Final model OR (95% CI) p-value Had financial needs 4.35 (1.85,10.20) &lt;.001

Dependence Modeling for Tsunami and Earthquake Disasters in the Indonesian Megathrust Zones using Copula Models

The megathrust earthquake parameters that are related to the number of tsunami disasters (𝑍) are the number of earthquakes (𝑋) and the maximum earthquake magnitude (𝑌). The dependence property of these three random variables is stochastic due to the uncertainty of each event. This study provides the stochastic dependence model of (𝑋, 𝑍) and (𝑌, 𝑍) based on the historical data of tsunami and megathrust earthquake disasters occurring from 1905 to 2022 in five megathrust zones of Indonesia, namely the Sumatra, Java, Bali, Sulawesi and Papua zones. In this study, the stochastic dependence models applied are bivariate Copula models that are flexible under rigid assumptions. The data source is taken from the U.S. Geological Survey catalog. The results show that each megathrust zone has various responses to the earthquake and tsunami mechanisms; it can be seen from the probability functions of three random variables in each megathrust zone that they are significantly different. Furthermore, according to stochastic dependence modeling results, it is found that the Copula model selected for each zone varies in type and parameters. Moreover, the selected bivariate Copula models for each megathrust zone have better agreement with the data modeled than the conventional bivariate discrete models.

Vibration-controlled transient elastography for significant fibrosis in treatment-naïve chronic hepatitis B patients: A systematic review and meta-analysis.

Accurate diagnosis of significant liver fibrosis in patients with chronic hepatitis B (CHB) is crucial when determining whether to initiate antiviral treatment (AVT). We conduct a meta-analysis to assess the diagnostic performance of vibration-controlled transient elastography (VCTE) for significant liver fibrosis in AVT-naïve CHB patients with serum alanine transaminase (ALT) levels within 5-fold the upper limit of normal (ULN). The Ovid-Medline, EMBASE, Cochrane, and KoreaMed databases were searched to identify studies that compared the performance of VCTE and liver biopsy (reference standard) when diagnosing significant liver fibrosis (≥F2) in AVT-naïve CHB patients with ALT within 5-fold the ULN. A hierarchical summary receiver operating characteristic curve (HSROC) and bivariate model were performed to evaluate the diagnostic performance of VCTE in the meta-analysis. Eight studies (2,003 patients) were included. The summary sensitivity and specificity for diagnosis of significant liver fibrosis were 0.78 (95% confidence interval [CI], 0.66-0.86) and 0.72 (95% CI, 0.60-0.82), respectively. The HSROC for the diagnosis of significant liver fibrosis was 0.81 (95% CI, 0.72-0.86). The optimal cutoff value of VCTE for diagnosis of significant liver fibrosis was 7.7 kPa with a sensitivity of 0.64 (95% CI, 0.50-0.76) and specificity of 0.83 (95% CI, 0.72-0.90). Our study demonstrated that VCTE has an acceptable diagnostic performance for significant liver fibrosis in AVT-naïve CHB patients with ALT within 5-fold the ULN.

Influence of socio-contextual factors on the link between traditional and new media use, and young people’s sexual risk behaviour in Sub-Saharan Africa: a secondary data analysis

BackgroundTraditional and new media use links to young people’s sexual risk behaviour. The social contexts of young people’s daily lives that influence media use and sexual risk behaviour are often investigated as independent causal mechanisms. We examined the link between media use and young people’s sexual risk behaviour, considering the intersecting socio-contextual factors in Sub-Saharan Africa.MethodsAge-adjusted bivariate logistic regression models tested the association between traditional media (TV, radio, and newspapers), and new media (mobile phone and online) use and sexual risk behaviour using the Demographic and Health Surveys from six Sub-Saharan African countries among unmarried sexually active youths, aged 15–24 years. Multivariate logistic regression models ascertained the media sources that had an additional influence on young people’s sexual risk behaviour, after accounting for socio-contextual factors, and knowledge about HIV and other sexually transmitted infections.ResultsSocio-contextual factors attenuated the association between media use and young people’s sexual risk behaviour in many countries. However, those who did not have access to new and traditional media were more likely to use unreliable contraceptive methods or not use contraception. Adolescents in Nigeria who did not own phones were 89% more likely to use unreliable contraceptive methods or not use any methods [(AOR = 1.89 (1.40–2.56), p < .001)], those in Angola who did not read newspapers had higher odds of not using contraception or used unreliable methods [(aOR = 1.65 (1.26–2.15), p < .001)]. Young people in Angola (aOR = 0.68 (0.56–0.83), p < .001), Cameroon [(aOR = 0.66 (0.51–0.84), p < .001)], Nigeria [(aOR = 0.72 (0.56–0.93), p = .01)], and South Africa [(aOR = 0.69 (0.49–0.98), p = .03)] who did not own phones were less likely to have 2 or more sexual partners compared to those who owned phones. Lack of internet access in Mali was associated with lower odds of having 2 or more sexual partners (aOR = 0.45 (0.29–0.70), p < .001). Traditional media use was significantly associated with transactional sex in many countries.ConclusionsMedia use is linked to sexual risk behaviour among young people in Sub-Saharan Africa. Socioeconomic inequalities, levels of globalization, as well as rural–urban disparities in access to media, underscore the need to deliver tailored and targeted sexual risk reduction interventions to young people using both traditional and new media.

Spatial distribution and topographic gradient effects of habitat quality in the Chang-Zhu-Tan Urban Agglomeration, China

This study aimed to analyze spatio-temporal changes in habitat quality in Chang-Zhu-Tan Urban Agglomeration during the 2000–2020 period and explore its topographic gradient effects. Using land use data from this period, the InVEST model was employed to assess the spatio-temporal variations in habitat quality. The bivariate spatial autocorrelation model was used to analyze the spatial correlation characteristics between habitat quality and various topographical factors. Additionally, terrain factor analysis was utilized to study the terrain gradient effects on habitat quality in the study area. The results reveal that: (1) The primary land use changes in the study area from 2000 to 2020 predominantly involve substantial arable land and forest conversions into urban development. (2) The average habitat quality indices for 2000, 2010, and 2020 in the Chang-Zhu-Tan Urban Agglomeration stand at 0.651, 0.622, and 0.606, respectively, indicating a consistent declining trend in habitat quality. The distribution of habitat quality grades demonstrates a spatial pattern of “lower in the central surroundings, higher in the surroundings.” (3) The Chang-Zhu-Tan Urban Agglomeration shows significant positive correlations between habitat quality and topographical gradients. Spatial aggregation tendencies between habitat quality and topographical gradients primarily exhibit “high-high” and “low-low” clustering. (4) The habitat quality of the Chang-Zhu-Tan urban agglomeration exhibits a significant topographic gradient effect, primarily characterized by an increase in habitat quality with the rise of the topographic gradient. The study outcomes contribute to unveiling the spatiotemporal variations in habitat quality within the Chang-Zhu-Tan Urban Agglomeration. Moreover, leveraging different habitat types’ distinctive terrain distribution characteristics, it proposes targeted habitat conservation measures, thereby offering theoretical support for biodiversity conservation and territorial spatial planning in the study area.

Patient-Reported Outcomes of Depression and Fibromyalgia Symptoms Do Not Predict Non-Inflammatory versus Inflammatory Diagnoses at Initial Rheumatology Consultation.

The objective of this study was to assess the potential value of patient-reported outcomes (PROs) of depression, fibromyalgia symptoms, and pain in predicting non-inflammatory vs. inflammatory diagnoses in rheumatology patients. This retrospective, single-center study evaluated electronic health record (EHR) data from adults who were seen for their first rheumatology consultation and subsequently received a diagnosis of an inflammatory (e.g., rheumatoid arthritis or spondyloarthritis) or non-inflammatory (e.g., osteoarthritis or fibromyalgia) condition. The PROs evaluated included depressive symptoms (Patient Health Questionnaire-2 [PHQ-2]), fibromyalgia symptom severity (FM SS), and pain. A total of 3669 patients were evaluated, including patients with (n = 984; 26.82%) and without (n = 2685; 73.18%) inflammatory rheumatologic disease, of whom 141 (3.8%) had fibromyalgia. The non-inflammatory subgroup reported higher FM SS scores, and the inflammatory subgroup had higher pain and inflammatory markers. Bivariate models based on PHQ-2 and FM SS had a very low specificity (0.3%) for predicting non-inflammatory conditions, resulting in the misclassification of >99% of inflammatory cases. Adding pain, inflammatory markers, and other relevant EHR variables increased specificity but still resulted in a high level of misclassification. The PROs evaluated in this study are not suitable for predicting non-inflammatory vs. inflammatory rheumatologic disease, even when combined with other EHR variables.

Postoperative delirium among elderly elective orthopedic patients in Addis Ababa Ethiopia: a multicentere longitudinal study

BackgroundDelirium is a neurocognitive disorder characterized by an acute and relatively rapid decline in cognition, disturbance of consciousness, reduced ability to focus, and shift of attention. It mainly affects elderly patients with an incidence of about 8–23% after an operation. It frequently occurs between 24-hrs and 5 days after surgery. It results in serious medical management problems. Hence, identifying the incidence and associated factors may help prevent and manage its sequel in the elderly.ObjectiveAssessment of the incidence and associated factors of postoperative delirium(POD) among elderly elective orthopedic surgical patients in Addis Ababa public hospitals, Ethiopia, 2024.MethodsA multi-centered longitudinal study was conducted on 220 elderly (age ≥ 65 years) patients in four selected public hospitals of the study area from February 2024 to May 2024, and a systematic sampling technique was used to select the study units. Data was collected through chart review and interviews of patients, and postoperative delirium was assessed using the confusion assessment method (CAM). Both bivariable and multivariable logistic regression models were used for statistical analysis. The strength of association was determined with an adjusted odds ratio (AOR) with a 95% confidence interval(CI) at a p-value of < 0.05.ResultsA total of 220 patients were studied, and the incidence of POD among elderly elective orthopedic surgical patients was 33.7%. Age 65–75(AOR = 0.47, 95%CI (0.226–0.97)), Induction using ketamine (AOR = 1.32, 95%CI(1.109–3.87), p = 0.003)), perioperative opioid use (AOR = 2.20, 95%CI(1.073 4.5313)), intraoperative anticholinergic use(AOR = 2.24,95%CI(1.831–4.235)), recent hospitalization history (AOR = 2.24,95%CI(1.202–4.206)), and transfusion (AOR = 2.83,95%CI(1.295–6.193)) were significantly associated with POD (p < 0.05).Conclusion and recommendationsThe incidence of POD in the study area was high (33.7%); advanced age, hospitalization history, Anesthesia induction by Ketamine, perioperative anticholinergic uses, opioid use, and blood transfusion use were associated factors for postoperative delirium. We recommend giving due attention to elderly patients with advanced age, history of hospitalization, perioperative Ketamie use, perioperative anticholinergic uses, opioid use, and blood transfusion use undergoing elderly elective orthopedic surgery.

Arts, culture and sports engagement and self-rated health: a cross-sectional population-based study in southern Sweden

BackgroundInternational research demonstrates an association between arts and culture activities and health and wellbeing. A similar association exists for sports event attendance and health. The aim of this study was to investigate associations between arts and culture engagement and attending sports events during the past year and self-rated health (SRH).MethodsA cross-sectional study. A public health survey with three reminders was sent to a stratified random sample of the adult 18–84 population in Scania in the southernmost part of Sweden in October-December 2019. The weighted response rate was 44%, and 40,087 total respondents were included in the present study. Analyses were performed in logistic regression models with multiple adjustments for age, education, country of birth, leisure-time physical activity (LTPA), smoking, alcohol consumption, and economic stress.ResultsThe prevalence of poor SRH was 32.8% among women and 27.6% among men. The prevalence of theatre/cinema attendance was 63.2% among women and 55.2% among men, arts exhibition/museum attendance was 41.0% among women and 36.0% among men, and for sports attendance it was 33.8% among women and 48.2% among men. All items included in the final models showed statistically significant associations with self-rated health in bivariate logistic regression models. In the multiple model, adjusted for all covariates including both men and women, the odds ratios (ORs) of poor SRH were statistically significant OR 1.21 (95% confidence interval: 1.14–1.29) for not visiting theatre/cinema during the past year, OR 1.11 (1.04–1.17) for not visiting arts exhibition and OR 1.31 (1.24–1.39) for not visiting a sports event.ConclusionsSignificant associations between arts and culture engagement and sports event attendance, and SRH were observed, although effect measures were comparatively low for arts and cultural engagement. The results may be useful for informing public health promotion and prevention strategies.

Some bivariate Schur-constant distributions and application to life insurance

Schur-constant models play a particular role when modelling time in fields such as actuarial science, insurance, reliability and survival models. These models describe random lifetimes with a certain dependence. In this study, a relation between proportional hazard rate distributions and Schur-constant models is established. Bivariate Schur-constant models, whose marginals are proportional hazard rate distributed, are introduced. Then, the dependency analysis in life insurances is performed through Schur-constant and copula models. It is revealed that there are differences in pricing when individuals' future lifetimes are dependent.