Log-linear Research Articles

Breast cancer treatment access disparities: A retrospective cohort study of breast cancer in patients treated at a high-complex cancer center in southern Brazil.

e13689 Background: More than seventy-three thousand new breast cancer cases are expected in Brazil for the year 2023, representing the most common malignancy in this country. Delaying time to treatment initiation has been associated with increased risk of worse outcomes. The Brazilian government developed several initiatives to accelerate the access of cancer patients to treatment in an adequate time-bound. One of these is a federal law defining that oncological treatment should begin within 60 days of pathological diagnosis. Methods: This retrospective study analyzed data of newly diagnosed breast cancer patients in 2022–2023 in Hospital de Clinicas de Porto Alegre (HCPA), a public hospital in Porto Alegre, Brazil. The primary objective was to build a predictive model of risk factors that could delay the time to first treatment beyond 60 days from diagnosis. The present analysis describes the socio-demographic characteristics of these patients and explores their impact on the time to oncologic treatment initiation. This project was approved by the Ethics and Research Committee (registration CAAE 71160423.7.0000.5327). Results: 184 patients who started their oncological treatment between 2022-2023 in HCPA were enrolled; 32 patients (17,3%) had their first treatment after 60 days from the diagnosis while 152 (82,7%) were treated before 60 days; 106 (57,3%) patients had studied up to elementary school and 32 (17,3%) were non-white; 53 patients (23%) had been submitted to biopsy outside HCPA. Patients who started their first treatment before 60 days had a mean of 38 days from diagnosis to first treatment while those treated after 60 days had a mean of 75,6 days. To evaluate how socio-demographic factors impacted the time to treatment initiation, a multivariate Poisson log-linear model adjusted for race, city of residence, stage of the disease, and type of first treatment considered different variables. Higher educational level had a statistically significant effect, with a rate ratio (RR) of 0.32 (95% CI 0.157 - 0.650, p < 0.05). We also found that performing biopsy in our institution instead of doing it elsewhere had a statistically significant impact on the time to first treatment, with an RR of 0.512 (95% CI 0.274 - 0.957, p = 0.036). Ethnicity was not related to delay of treatment (p-value=0.125). Conclusions: This study identified that socio-demographic factors are crucial to guarantee the appropriate time to start treatment for breast cancer patients in a middle-income country. Higher educational level had a positive impact on time-to-treatment initiation, as well as to perform biopsy in the same institution patients were treated. In this first analysis, ethnicity, clinical staging, and type of first treatment did not meet the statistical criteria to be considered relevant and the accrual of more patients is needed for further conclusions.

Assessing the environmental and downstream human health impacts of decentralizing cancer care.

1522 Background: Greenhouse gas emissions from healthcare are substantial and harm persons with cancer. Emissions from outpatient cancer care visits are not well described, nor are the downstream reduction in human harms that could be obtained through visit “decentralization” (telemedicine and local care when possible). Methods: This life-cycle assessment (LCA)-based study evaluated changes in emissions and downstream health harms associated with (1) telemedicine visits using retrospective observational analysis and (2) fully decentralized visits using counterfactual modeling. The retrospective observational cohort included persons receiving cancer care at Dana-Farber Cancer Institute (DFCI) and 20 affiliated facilities between 5/2015-12/2020. The main outcome was the adjusted per visit-day difference in emissions (in kilograms carbon dioxide equivalents: kgCO2e) between two periods: an in-person care period (5/2015-2/2020; “Pre”) and a telemedicine period (3/2020-12/2020; “Post”). Mixed effects log-linear model assessed emissions changes adjusted for age, sex, race, ethnicity, and cancer type, with random effects on person. The counterfactual model assessed emissions changes between actual in-person visits during the Pre period and a counterfactual with maximal decentralization. Visit-day eligibility for decentralization was obtained by categorizing appointments (e.g., clinician visit, infusion) as DFCI required, local care possible, or telemedicine possible. This cohort was matched to a national population diagnosed with cancer over the same period (Cancer in North America [CiNA] dataset) using mixed-effects linear modeling, through which annual changes in disability-adjusted life-years (DALY) from clinician visit decentralization were estimated using Eckelman’s mortality cost of carbon conversion. Results: There were123,890 unique patients in the DFCI cohort seen over 1.6 million visit-days (Pre N=110,180, Post N=61,691) at a median of 6 visit-days per patient (IQR 2, 15). An estimated 72,554,006 kgCO2e were within scope of the LCA emitted during the study period. In mixed-effects log-linear regression, the adjusted mean absolute reduction in per visit-day emissions between Pre and Post periods was 36.4 kgCO2e (95%CI 36.2,36.6), or a reduction of 81.3% (95%CI 80.8,81.7) compared to the baseline model. In the counterfactual decentralized care model of the Pre period, there was a relative emissions reduction of 33.1% (95%CI 32.9,33.3). When demographically matched to 10.3 million persons in the CiNA dataset, decentralized care would have reduced national emissions by 75.3 million kgCO2e annually; this corresponds to an estimated annual reduction of 15.0-47.7 DALYs. Conclusions: Employing decentralization through telemedicine and local care can substantially reduce emissions during cancer care delivery; this corresponds to a small reduction in human mortality.

Impact Analysis of the Law on Diminishing Returns on the Mass Appraisal of Real Estate in the Republic of Moldova

The present study investigates the shortcomings of the linear models of massive evaluation of real estate in the Republic of Moldova, currently used to determine the taxable value, the author noting, in particular, the influence of the distortion of the calculated values, within the mathematical modeling and the need to respect the law of diminishing returns. The challenges are relevant for countries with an ad-valorem taxation system, such as the Republic of Moldova, which needs to harmonize its national legislation with the criteria for joining the European Union. The study uses the system of mass evaluation of real estate properties in order to identify and develop optimization solutions for the massive evaluation system of real estate properties, in order to tax them, by implementing log-linear models, with effective results compared to existing linear regressions. By benchmarking performance metrics between linear regressions from existing and refined models, the research improves the taxation system through more accurate methodologies.

Food Insecurity in Hispanic Populations Is Associated with an Increased Risk of Hepatic Steatosis: A Nationally Representative Study.

Introduction: The Hispanic population in the US faces a higher risk of nonalcoholic fatty liver disease (NAFLD). Multiple factors influence this risk, including genetics, environmental factors, and socioeconomic statuses. Inadequate access to nutritious foods, or food insecurity, is prevalent among Hispanic individuals and poses a metabolic risk for both the onset and development of NAFLD. Materials and Methods: We utilized the National Health and Nutrition Examination Survey (NHANES) 2017-2020 pre-pandemic data to analyze the association between Hispanic ethnicity, hepatic steatosis, fibrosis, and food insecurity. Vibration-controlled transient elastography (VCTE) was employed to assess liver stiffness (LSM) and controlled attenuation parameter (CAP) scores to determine fibrosis and steatosis, respectively. Linear and ordinal logistic regression models were applied to their continuous, log-transformed, and categorical forms, adjusting for demographics, metabolic comorbidities, and socioeconomic factors. Models were subsequently stratified based on food security statuses. Results: A total of 7396 Hispanic participants were included in the study. Under multivariable analysis, Hispanic individuals had higher CAP scores (Beta-coefficient: 10.2 dB/m, 95% CI: 6.1-14.4 dB/m, p = 0.001)) vs. non-Hispanic individuals, without statistically significant differences in fibrosis. Food-insecure participants exhibited higher CAP scores than their food-secure counterparts. After stratification, a stronger association between Hispanic ethnicity and CAP scores was evident in the food-insecure group (Beta-coefficient: 11.8 dB/m, 95% CI: 4.4-19.3 dB/m, p = 0.003). Discussion: This study demonstrates the heightened risk of hepatic steatosis among individuals with Hispanic ancestry in the US. The risk is exacerbated by food insecurity, particularly for Hispanic individuals. The contribution is linked to the dietary habits in this population that lead to metabolic risk factors associated with hepatic steatosis. Considering the rising prevalence of NAFLD and food insecurity, interventions focusing on nutritional support and healthcare access among this population could mitigate these burdens.

Social Capital and Poverty Reduction in Ethiopia: Evidence from the Amhara Region

This paper broadens the scope of research on social capital theory by offering new perspectives and empirical evidence on reducing objective poverty. The aim of this study is to investigate the influence of social capital on poverty reduction among members of financial cooperatives in both urban and rural areas of the Amhara National Regional State, Ethiopia. Kothari's formula was employed, followed by multi-stage stratified, proportional, and random sampling. Primary data was collected from 348 sample members through a structured questionnaire, focus group discussions, and personal interviews. Additionally, data was analyzed using multiple linear regression and logistic regression models. The study reveals important insights into the relationship between social capital and poverty reduction among members. Structural and relational social capital, family labor, physical capital, and access to credit have a positive and significant impact on poverty reduction. On the other hand, the lack of cognitive social capital, which refers to the lack of awareness regarding the common mission, goals, and shared values of financial cooperatives, has a negative and significant impact on poverty reduction. Furthermore, family size, marital status, and individual health conditions also negatively and significantly affect poverty reduction. The study emphasizes the significance of social capital in influencing poverty reduction among members in the study area. Policymakers can design targeted interventions to effectively combat poverty by recognizing the impact of different dimensions of social capital, as well as family labor and physical capital. Strengthening social capital within financial cooperatives and promoting collaboration with financial institutions are essential steps towards achieving the Sustainable Development Goal of poverty alleviation in the region.

Machine Learning to Predict Pregnancy in Dairy Cows: An Approach Integrating Automated Activity Monitoring and On-Farm Data.

Automated activity monitoring (AAM) systems are critical in the dairy industry for detecting estrus and optimizing the timing of artificial insemination (AI), thus enhancing pregnancy success rates in cows. This study developed a predictive model to improve pregnancy success by integrating AAM data with cow-specific and environmental factors. Utilizing data from 1,054 cows, this study compared the pregnancy outcomes between two AI timings-8 or 10 h post-AAM alarm. Variables such as age, parity, body condition, locomotion, and vaginal discharge scores, peripartum diseases, the breeding program, the bull used for AI, milk production at the time of AI, and environmental conditions (season, relative humidity, and temperature-humidity index) were considered alongside the AAM data on rumination, activity, and estrus intensity. Six predictive models were assessed to determine their efficacy in predicting pregnancy success: logistic regression, Bagged AdaBoost algorithm, linear discriminant, random forest, support vector machine, and Bagged Classification Tree. Integrating the on-farm data with AAM significantly enhanced the pregnancy prediction accuracy at AI compared to using AAM data alone. The random forest models showed a superior performance, with the highest Kappa statistic and lowest false positive rates. The linear discriminant and logistic regression models demonstrated the best accuracy, minimal false negatives, and the highest area under the curve. These findings suggest that combining on-farm and AAM data can significantly improve reproductive management in the dairy industry.

Association between exposure to per- and polyfluoroalkyl substance and liver injury in American adults.

Epidemiological data is scarce regarding the association between exposure to mixtures of per- and polyfluoroalkyl substances (PFASs) and liver injury in the general populace. The current research used data from the National Health and Nutrition Examination Survey (2009-2018). The PFAS exposure levels were defined by the serum concentrations of PFASs with > 70% detection in samples, namely perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorohexane sulfonic acid (PFHxS), perfluorodecanoic acid (PFDeA), and perfluorooctane sulfonic acid (PFOS). Liver injury was assessed from two aspects: first, the degree of liver inflammation was determined based on serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamyltransferase (GGT), and total bilirubin (TBIL) levels; second, the degree of liver fibrosis was determined based on fibrosis-4 (FIB-4) index. We assessed the associations between individual or total PFAS exposure and these outcomes using multivariable linear regression models and logistic regression models, restricted cubic splines, and weighted quantile sum regression. Among the samples of 7484 American adults, the median concentration of PFOS was the highest, followed by PFOA and PFHxS. Using multivariable linear regression, a positive correlation was observed between all PFASs and liver enzymes such as ALT, AST, and TBIL. Additionally, the weighted quantile sum model indicated an overall positive association between the five PFASs and liver injury indicators. For liver function biomarkers and liver fibrosis, PFNA and PFOS were the most heavily weighting chemicals, respectively. Our findings provide new epidemiological evidence indicating a potential association between PFAS exposure and adverse effects on liver injury biomarkers, highlighting the potentially harmful effects of PFAS exposure on liver health.

Log-Linear Model and Delivery Load Analysis for Improvements in Water Quality through TMDL in the Gyeongan Stream Watershed, Republic of Korea

The effectiveness of implementing the total maximum daily load (TMDL) in the Gyeongan stream watershed was evaluated to assess its impact on water quality. The relationships between water quality and flow rate and load and water quality were reinterpreted using a log-linear model and the delivery load, respectively. To estimate annual water quality trends and analyze the effects of water quality improvement in each parameter, an improved multivariable log-linear model addressing the limitations of the traditional L-Q equation was applied to analyze the relationship between water quality and flow rate, excluding the effects of flow rate and seasonality. The effect of total phosphorus (T-P) was particularly prominent. A new delivery load was developed and applied to address the limitations of the original unit-based delivery load. Evaluations showed that water quality continuously improved across all parameters, and all methods (excluding the influence of flow rate on water quality fluctuations) were highly effective in estimating water quality changes attributable to anthropogenic pollution sources. The analysis of pollutant contributions revealed that managing point sources is necessary for controlling the biochemical oxygen demand and total nitrogen, while point and non-point sources require T-P management. Future policy development should consider this when formulating management strategies.

The Inverted U-Shaped Association between Serum Vitamin D and Serum Uric Acid Status in Children and Adolescents: A Large Cross-Sectional and Longitudinal Analysis.

Serum vitamin D is associated with hyperuricemia. However, previous studies have been controversial, with limited focus on children and adolescents. This study aimed to examine the cross-sectional and longitudinal associations between serum vitamin D and serum uric acid (SUA) levels in children and adolescents. The cross-sectional survey comprised 4777 participants aged 6 to 18 years, while the longitudinal survey involved 1641 participants aged 6 to 12 years, all derived from an ongoing cohort study in Shenzhen, China. Restricted cubic splines were used to visualize the dose-response relationship between vitamin D and SUA and the risk of higher SUA status. Two-segment generalized linear models (GLM) and logistic models were used to assess the association between vitamin D and SUA and higher SUA status, respectively. The longitudinal analysis used GLM. We observed an inverted U-shaped relationship between vitamin D and SUA (p-overall < 0.0001, p-nonlinear = 0.0002), as well as the risk of higher SUA status (p-overall = 0.0054, p-nonlinear = 0.0015), with the vitamin D inflection point at 24.31 and 21.29 ng/mL, respectively. A 10 ng/mL increment in 25(OH)D3 levels, when below 20.92 ng/mL, was associated with a 68% rise in the risk of higher SUA status (OR: 1.68, 95%CI: 1.07-2.66). Conversely, when 25(OH)D3 levels were above or equal to 20.92 ng/mL, a 10 ng/mL increment was associated with a 45% reduction risk of higher SUA status (OR: 0.55, 95%CI: 0.36-0.84). Longitudinal analysis indicated that the annual change of SUA was from -4.80 (β, 95%CI: -10.74, 1.13) to -9.00 (β, 95%CI: -15.03, -2.99) and then to -6.77 (β, 95%CI: -12.83, -0.71, p for trend = 0.0212) μmol/L when increasing the quartile of vitamin D3. An inverse U-shaped relationship was observed between vitamin D and SUA as well as the risk of higher SUA status. Sufficient vitamin D levels appear to play a preventative role against the age-related increase in SUA. Ensuring adequate vitamin D levels may be beneficial in improving uric acid metabolism.

Acquisition of key clinical communication skills through simulation-based education: findings from a program for postgraduate psychiatry trainees (ComPsych)

ObjectiveFew studies have investigated the maintenance of skills acquired in classroom-based clinician education. Using an advanced simulation-based clinical communication skill training program for postgraduate psychiatry education (ComPsych), we aimed to investigate skill acquisition through assessing changes in competence (abilities) and performance (practice).MethodsForty trainee psychiatrists (15 males; age range 26–48) participated. Video-recorded Standardized Patient Assessments (SPAs) were delivered twice pre- and post-training to assess learning. Skills were coded by independent psychologists using the Core Communication Skills (CCS) coding system. Simulated patients (SPs) rated trainees' communication performance using the Sim-Patient SPA checklist. Paired t-tests, linear mixed models and logistic mixed models assessed changes in communication skills over time.ResultsFor SPAs, reliability of coder ratings was deemed acceptable (ICC range 0.67 to 0.87). Mean post-training communication performance significantly increased for skills in agenda setting (p < 0.001), information organization (p < 0.001), empathic skills (p = 0.046), and overall skills performance (p = 0.001). Significant decreases for questioning skills were indicative of reduced reliance on these skills post-training. SPs rated all skillsets higher post-training. A modest relationship was detected between frequency (coded) and (SP-rated) quality of communication skills. Improvements in agenda setting and information organisation skills were retained ~ 6 weeks post-training.ConclusionsTraining improved patient-centered communication skills in psychiatry trainees, particularly skills in agenda setting and information organization, with skills retained ~ 6 weeks post-training. There was reduced reliance on questioning skills, which are well utilised generally. The study supports the benefits of this method of communication skills training into postgraduate psychiatry education.

Impact of Government Funded Health Insurance Scheme on OOP and Quality of Health Care: A Study of Maternal Health Care in Rajasthan

There has been a gradual shift of India’s health policies in favour of government-funded health insurance schemes rather than investment in public health facilities. The impact of this shift on quality of health care, especially for the poor and vulnerable population, is yet to be fully understood. The current study has been undertaken to study the effectiveness of one such state government-funded health insurance scheme, known as Bhamashah Swasthya Bima Yojana (BSBY), on out-of-pocket (OOP) expenditure and quality of health care services for the child delivery cases in a low-income community in the capital city of Jaipur in Rajasthan, India. While this study contributes to knowledge on the impact of access to health insurance on OOP expenditure, it covers a critical gap in the literature regarding its effect on quality of health care. The empirical analysis, conducted using log-linear and logit models, indicates that BSBY has a positive impact on reduction of OOP and improvement in quality of treatment in the study area.

Application of UV LEDs to inactivate antibiotic resistant bacteria: Kinetics, efficiencies, and reactivations

Unregulated antibiotic use has led to the proliferation of antibiotic-resistant bacteria (ARB) in aquatic environments. Ultraviolet light-emitting diodes (UV LEDs) have evolved as an innovative technology for inactivating microorganisms offering several advantages over traditional mercury lamps. This research concentrated on utilizing UV LEDs with three distinct wavelengths (265 nm, 275 nm, and 285 nm) to inactivate E. coli DH10β encoding the ampicillin-resistant blaTEM-1 gene in its plasmid. Non-linear models, such as Geeraerd's and Weibull, provided more accurate characterization of the inactivation profiles than the traditional log-linear model due to the incorporation of both biological mechanisms and a deterministic approach within non-linear models. The inactivation rates of ARB were higher than antibiotic-sensitive bacteria (ASB) when subjected to UV LEDs. The highest inactivation rates were observed when all microorganisms were exposed to 265 nm. Photoreactivation emerged as the primary mechanism responsible for repairing DNA damage induced by UV LEDs. 285 nm showed the highest reactivation efficiencies for ARB under different fluences. At higher fluences, both 265 and 275 nm displayed similar effectiveness in suppressing reactivation, while at lower fluences, 275 nm exhibited better efficacies in controlling the reactivation. Therefore, the inhibition of reactivation was influenced by the extent of damage incurred to both DNA and enzymes. In nutrient-poor media (0.9 % NaCl), ASB did not exhibit any reactivation potential. However, the addition of Luria-Bertani (LB) broth promoted the reactivation of ASB. Lower fluence rate was more beneficial at 265 nm whereas higher fluence rates were more effective for longer wavelengths. The inactivation of ARB was enhanced by dissolved organic carbon (DOC) at low fluences. However, the removal of ARB was reduced due to the presence of DOC at higher fluences. The highest energy demand for ARB inactivation was reported at 285 nm. Environmental implicationThe excessive and unregulated utilization of antibiotics has emerged as a significant issue for public health. This paper presents a comprehensive analysis of the effectiveness of UV LEDs, an emerging technology, in the inactivation of antibiotic-resistant bacteria (ARB). This research paper explores the kinetics of UV LEDs with different wavelengths to inactivate ARB along with the reactivation efficiencies. This research work also explores the impact and relevant mechanisms of the impact of dissolved organic carbon (DOC) on the inactivation of ARB by UV LEDs.

Deriving biomass conversion factors for southern temperate benthic fauna; analytical methods matter

Biomass is a fundamental ecological measure used to quantify ecosystem structure and function. It is costly to measure but can be estimated using conversion factors based on established relationships between different biomass measures, however such conversion factors may not be applicable across broad geographic regions. For temperate benthic fauna, currently available mass-to-mass conversion factors were largely established in Northern Hemisphere ecosystems. Here, we present conversion factors for temperate Australian benthic fauna typically found in microtidal coastal bays and estuaries (14 taxa encompassing five classes: Polychaeta; Bivalvia; Gastropoda; Crustacea; Insecta). We derived 126 conversion factors using two statistical techniques between several mass measures (e.g. wet mass, dry mass, ash-free dry mass, shell-free masses) with specimens from three preservation methods (ethanol, formalin, frozen). Our conversion factors were generally not congruent with those obtained from the literature. We also found that the choice of prediction method used to derive conversion factors can be a substantial source of error in biomass estimation that has largely been overlooked in mass-to-mass conversion. Log-linear ordinary least squares regression models provided substantially more accurate predictions than simple mean ratios. We outline an analytical approach for future use to derive more globally comparable conversion factors for estuarine benthic fauna.

Changing Trends in the Global Disease Burden of Pancreatic Cancer from 1990 to 2030.

To explore the global burden of pancreatic cancer (PC) from 1990 to 2019, evaluate independent effects of age, period, and cohort on the incidence of PC, and predict the incidence of PC in the next decade. Data were obtained from the Global Burden of Disease Study 2019. We calculated the age-standardized disability-adjusted life years (DALY) rate, age-standardized mortality rate (ASMR), age-standardized incidence rate (ASIR), and age-standardized prevalence rate (ASPR) of PC. Joinpoint Poisson regression analysis was performed to identify the temporal trends in the incidence of PC. Then, a two-factor model was constructed using the Poisson log-linear model, and a three-factor model was constructed using the intrinsic estimator (IE) method to estimate the independent effects of age, period, and cohort on the incidence of PC. Finally, the Bayesian age-period-cohort (BAPC) model was also used to predict the age-standardized global incidence rate of PC and age-standardized new PC cases from 2020 to 2030. Overall, the DALY rate, ASMR, ASIR, and ASPR all increased from 1990 to 2019. The ASIR in males increased from 6 per 100,000 in 1990 to 7.5 per 100,000 in 2019 and was predicted to rise to 8.2 per 100,000 by 2030. Meanwhile, the ASIR in females rose from 4.5 per 100,000 in 1990 to 5.7 per 100,000 in 2019 and was predicted to rise to 6.3 per 100,000 by 2030. The age effect on the incidence of PC showed sharp increasing trends from 40 to 79years. The period effect continuously increased with advancing periods, but the cohort effect showed substantial decreasing trends. The age and period effect on the incidence of PC presented increasing trends, while the cohort effect showed decreasing trends. All indicators of the global burden of PC are increasing in both males and females, and the ASIR is predicted to rise at an alarming rate by 2030. Thus, timely screening and intervention are recommended, especially for earlier birth cohorts at high risk.

Association between the triglyceride glucose index and obstructive sleep apnea and its symptoms: results from the NHANES

BackgroundCertain studies have indicated a link between obstructive sleep apnea and insulin resistance in specific populations. To gain more clarity, extensive research involving a broad sample of the overall population is essential. The primary objective of this study was to investigate this correlation by utilizing data from the National Health and Nutrition Examination Survey database.MethodsThe analysis incorporated data from the National Health and Nutrition Examination Survey database spanning the time periods from 2005 to 2008 and from 2015 to 2018, with a focus on American adults aged 18 years and older after applying weight adjustments. Key variables such as obstructive sleep apnea, triglyceride glucose index, and various confounding factors were considered. A generalized linear logistic regression model was used to investigate the association between obstructive sleep apnea and the triglyceride glucose index, with additional exploration of the consistency of the results through hierarchical analysis and other techniques.ResultsThe study included participants aged between 18 and 90 years, with an average age of 46.75 years. Among the total sample, 50.76% were male. The triglyceride glucose index demonstrated a diagnostic capability for obstructive sleep apnea, with an AUC of 0.701 (95% CI: 0.6619–0.688). According to the fully adjusted model, individuals in the fourth quartile of the triglyceride glucose index showed an increased likelihood of having obstructive sleep apnea compared to those in the first quartile (OR: 1.45; 95% CI: 1.02–2.06; P < 0.05). Subgroup analysis indicated that male sex (OR: 2.09; 95% CI: 1.76–2.45; P < 0.05), younger age (OR: 2.83; 95% CI: 2.02–3.96; P < 0.05), white ethnicity (OR: 2.29; 95% CI: 1.93–2.73; P < 0.05), and obesity (OR: 1.54; 95% CI: 1.28–1.85; P < 0.05) were correlated with an elevated risk of OSA.ConclusionsThis study demonstrated a strong association between an elevated TG index and OSA. Additionally, the triglyceride glucose index could serve as an independent predictor of obstructive sleep apnea.

Nonlinear relationship between oxidative balance score and hyperuricemia: analyses of NHANES 2007–2018

BackgroundLimited data regarding the correlation between oxidative balance score (OBS) and hyperuricemia highlights the necessity for thorough investigations. This study aims to examine the link between OBS, which incorporates dietary and lifestyle factors, and the occurrence of hyperuricemia.MethodsWe conducted a cross-sectional study involving 13,636 participants from the 2007–2018 National Health and Nutrition Examination Survey (NHANES). The oxidative balance score (OBS) was determined based on four lifestyle factors and sixteen dietary nutrients. We assessed the levels of serum uric acid (SUA) and the occurrence of hyperuricemia as outcomes. Weighted logistic regression and linear models were used for statistical analysis, using Restricted Cubic Splines (RCS) to examine potential nonlinear associations. Subgroup analysis and sensitivity assessments were performed to identify any variations and ensure the robustness of the findings.ResultsHigher OBS was consistently correlated with decreased SUA levels and a reduced prevalence of hyperuricemia. RCS highlighted a significant negative nonlinear association, particularly in females. Subgroup analysis revealed gender-based differences and interactive correlation, providing additional insights regarding OBS and hyperuricemia relationship.ConclusionThis study underscores a robust negative correlation between OBS and SUA levels as well as the incidence of hyperuricemia, emphasizing the importance of dietary and lifestyle factors. Incorporating RCS, subgroup analysis, and sensitivity assessments enhances the depth of our findings, providing valuable insights for further research.

The impact of provider-patient communication skills on primary healthcare quality and patient satisfaction in rural China: insights from a standardized patient study

ObjectivesIn middle-income countries, poor physician-patient communication remains a recognized barrier to enhancing healthcare quality and patient satisfaction. This study investigates the influence of provider-patient communication skills on healthcare quality and patient satisfaction in the rural primary healthcare setting in China.MethodsData were collected from 504 interactions across 348 rural primary healthcare facilities spanning 21 counties in three provinces. Using the Standardized Patient method, this study measured physician-patient communication behaviors, healthcare quality, and patient satisfaction. Communication skills were assessed using the SEGUE questionnaire framework. Multivariate linear regression models and multivariate logistic regression models, accounting for fixed effects, were employed to evaluate the impact of physicians’ communication skills on healthcare quality and patient satisfaction.ResultsThe findings indicated generally low provider-patient communication skills, with an average total score of 12.2 ± 2.8 (out of 24). Multivariate regression models, which accounted for physicians’ knowledge and other factors, demonstrated positive associations between physicians’ communication skills and healthcare quality, as well as patient satisfaction (P < 0.05). Heterogeneity analysis revealed stronger correlations among primary physicians with lower levels of clinical knowledge or more frequent training.ConclusionThis study emphasizes the importance of prioritizing provider-patient communication skills to enhance healthcare quality and patient satisfaction in rural Chinese primary care settings. It recommends that the Chinese government prioritize the enhancement of provider-patient communication skills to improve healthcare quality and patient satisfaction.

Increased regional body fat is associated with depressive symptoms: a cross-sectional analysis of NHANES data obtained during 2011–2018

AimsThe findings from previous epidemiological studies of the association between regional body fat and depressive symptoms have been unclear. We aimed to determine the association between the body fat in different regions and depressive symptoms based on data from the National Health and Nutrition Examination Survey (NHANES).MethodsThis study included 3393 participants aged ≥ 20 years from the NHANES performed during 2011–2018. Depressive symptoms were assessed using the Patient Health Questionnaire-9. The fat mass (FM) was measured in different regions using dual-energy X-ray absorptiometry to determine the total FM, trunk FM, arm FM, and leg FM. The FM index (FMI) was obtained by dividing the FM in kilograms by the square of the body height in meters. Weighted data were calculated in accordance with analytical guidelines. Linear logistic regression models were used to quantify the association between regional FMI and depressive symptoms. Univariate and stratified analyses were also performed.ResultsThe participants in this study comprised 2066 males and 1327 females. There were 404 (11.91%) participants with depressive symptoms, who were aged 40.89 ± 11.74 years and had a body mass index of 30.07 ± 7.82 kg/m². A significant association was found between total FMI and depressive symptoms. In the fully adjusted multivariate regression model, a higher total FMI (odds ratio = 2.18, 95% confidence interval [CI] = 1.08–4.39) was related to a higher risk of depressive symptoms, while increased total FMI (β = 1.55, 95% CI = 0.65–2.44, p = 0.001), trunk FMI (β = 0.57, 95% CI = 0.04–1.10, p = 0.036), and arm FMI (β = 0.96, 95% CI = 0.33–1.59, p = 0.004) were significantly associated with PHQ-9 (Patient Health Questionnaire-9) scores, whereas the leg FMI was not (p = 0.102). The weighted association between total FMI and depressive symptoms did not differ significantly between most of the subpopulations (all p values for interaction > 0.05). The risk of having depression was higher in individuals who were non-Hispanic Whites, smokers, drinkers, obese, and had diabetes and thyroid problems (p < 0.05).ConclusionThese findings suggest that the population with a higher regional FMI is more likely to have depressive symptoms, especially in those who also have an increased total FMI. The association is more pronounced in individuals who are smokers, drinkers, obese, and have diabetes and thyroid problems.

Federal Impacts on Buprenorphine Prescribing in Washington State, 2012 to 2022.

Objectives. To evaluate changes in monthly buprenorphine dispensation associated with federal prescribing policies in Washington State from 2012 to 2022. Methods. We conducted an interrupted time series analysis comparing monthly buprenorphine prescriptions dispensed per 1000 population after the Comprehensive Addiction and Recovery Act (CARA), Substance Use-Disorder Prevention That Promotes Opioid Recovery and Treatment for Patients and Communities Act (SUPPORT), and new prescribing rules during the COVID-19 pandemic. Buprenorphine formulated for opioid use disorder was included from the Washington State Prescription Monitoring Program. A log-linear autoregressive model measured linear trend changes. Results. Physician prescribing increased by 1.63% (95% confidence interval [CI] = 1.41%, 1.85%) per month after CARA with sustained declines after SUPPORT. Nurse practitioner (NP) prescribing increased by 19.48% (95% CI = 18.8%, 20.16%) per month after CARA with physician assistants (PAs) showing similar trends. Following the implementation of SUPPORT, NP and PA trends continued to increase at a reduced growth rate of 3.96% (95% CI = 2.01%, 5.94%) and 1.87% (95% CI = 0.56%, 3.19%), respectively. No prescribers experienced increases during the COVID-19 pandemic. Conclusions. CARA nearly tripled the buprenorphine prescribing rate. The SUPPORT Act initiated sustained declines for physician prescribing, and the COVID-19 period reversed gains for PAs and NPs. The current opioid crisis requires expanded efforts in Washington State. (Am J Public Health. 2024;114(7):696-704. https://doi.org/10.2105/AJPH.2024.307649).

Modeling thermal inactivation of Salmonella Enteritidis in ground chicken supplemented with a mixture of ribwort, sorrel, and yarrow extracts

AbstractThermal death kinetics of Salmonella Enteritidis in ground chicken in the presence of ribwort, sorrel and yarrow extracts mixture (1%) was investigated by fitting the inactivation curves to the log–linear and Weibull models. The thermal inactivation curves were fitted well to both models (r2 ≥ 0.94). The times required for 4–log reduction in the S. Enteritidis population were shortened by 47–64% in ground chicken supplemented with the herbal extract mixture (p &lt; 0.05). The 4–log reduction times calculated using the Weibull model were 0.13–13.6% longer than those extrapolated with the log–linear model. The z values in the ground chicken samples with and without herbal extract were 5.08°C (r2 = 0.97) and 5.57°C (r2= 0.94), respectively. The results suggest that the mixture of these extracts increased the thermal sensitivity of S. Enteritidis significantly at tested temperatures. In addition, using the Weibull model to calculate thermal death kinetics may reduce the underestimation of the thermal reduction times.Practical applicationsThis research aimed to investigate the effects of an herbal extract mixture consisting of ribwort, sorrel, and yarrow on the thermal resistance of Salmonella Enteritidis in ground chicken. While these plants are recognized for their antimicrobial and antioxidant properties, there are not many studies conducted to explore their effects on foodborne pathogens in the food matrix. As far as we know, this is the first study that examines the impact of these plants on the thermal resistance of S. Enteritidis in ground chicken. We determined the thermal death kinetics of S. Enteritidis in ground chicken with and without the herbal extract mixture using curve fitting to log‐linear and Weibull models. The findings of this study could help the food industry to develop cooking conditions for Salmonella‐free chicken products.