Use of Statistics in Plant Cell Tissue Culture.

Statistics and experimental design are important tools for plant cell and tissue culture researchers and should be used when planning and conducting experiments as well as during the analysis and interpretation of experimental results. The chapter provides basic concepts important to the statistical analysis of data obtained from plant tissue culture experiments and illustrates the application of common statistical procedures to analyze binomial, count, and continuous data for experiments with different treatment factors as well as identifying trends of dosage treatment factors.

A simple Cox approach to estimating risk ratios without sharing individual-level data in multi-site studies.

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration's Sentinel System.

Association of adverse childhood experiences with poor health condition among middle-aged and elderly adults in the United States: A nationally retrospective cohort study.

BACKGROUND: The specific effects of adverse childhood experiences (ACEs) in adulthood and senectitude were less known. We aim to examine the relationship between early ACEs and overall health condition as well as specific dimensions in the middle-aged and elderly population. METHODS: In the 2019-2021 Behavioral Risk Factor Surveillance System Study, robust Poisson regression models were used to estimate the relationship between ACE exposure and current health status among adults aged 45 ≥ years. RESULTS: Of the 195,472 participants, 53.8 % were female and the mean age was 65.0 years. Compared to populations without ACE, ACE exposures were more significantly associated with depression (PR: 2.03, 95 %CI: 1.94-2.21), frequent mental health (PR: 1.85, 95 %CI: 1.74-1.97) and subject cognitive decline (PR: 1.99, 95 %CI:1.85-2.14) than with physical health (PR: 1.37, 95 %CI: 1.32-1.44), with dose-response patterns. The association with mental disorder was especially significant among the elderly population. CONCLUSION: Early ACEs are associated with adverse health outcomes that persist into later life, particularly mental disorders and cognitive decline. Poor mental health may indirectly influence associations with ACEs and cognitive decline as well as physical health. Our findings emphasize the importance of lifelong psychological screening and support for the ACE-exposed middle-aged and elderly population.

Regression models for average hazard.

Limitations of using the traditional Cox's hazard ratio for summarizing the magnitude of the treatment effect on time-to-event outcomes have been widely discussed, and alternative measures that do not have such limitations are gaining attention. One of the alternative methods recently proposed, in a simple 2-sample comparison setting, uses the average hazard with survival weight (AH), which can be interpreted as the general censoring-free person-time incidence rate on a given time window. In this paper, we propose a new regression analysis approach for the AH with a truncation time τ. We investigate 3 versions of AH regression analysis, assuming (1) independent censoring, (2) group-specific censoring, and (3) covariate-dependent censoring. The proposed AH regression methods are closely related to robust Poisson regression. While the new approach needs to require a truncation time τ explicitly, it can be more robust than Poisson regression in the presence of censoring. With the AH regression approach, one can summarize the between-group treatment difference in both absolute difference and relative terms, adjusting for covariates that are associated with the outcome. This property will increase the likelihood that the treatment effect magnitude is correctly interpreted. The AH regression approach can be a useful alternative to the traditional Cox's hazard ratio approach for estimating and reporting the magnitude of the treatment effect on time-to-event outcomes.

Strategic HIV Case Findings among Infants at Different Entry Points of Health Facilities in Cameroon: Optimizing the Elimination of Mother-To-Child Transmission in Low- and- Middle-Income Countries.

BACKGROUND: HIV case finding is an essential component for ending AIDS, but there is limited evidence on the effectiveness of such a strategy in the pediatric population. We sought to determine HIV positivity rates among children according to entry points in Cameroon. METHODS: A facility-based survey was conducted from January 2015 to December 2019 among mother-child couples at various entry points of health facilities in six regions of Cameroon. A questionnaire was administered to parents/guardians. Children were tested by polymerase chain reaction (PCR). Positivity rates were compared between entry points. Associations were quantified using the unadjusted positivity ratio (PR) for univariate analyses and the adjusted positivity ratio (aPR) for multiple Poisson regression analyses with 95% confidence intervals (CIs). p-values < 0.05 were considered significant. RESULTS: Overall, 24,097 children were enrolled. Among them, 75.91% were tested through the HIV prevention of mother-to-child transmission (PMTCT) program, followed by outpatient (13.27%) and immunization (6.27%) services. In total, PMTCT, immunization, and outpatient services accounted for 95.39% of children. The overall positivity was 5.71%, with significant differences (p < 0.001) between entry points. Univariate analysis showed that inpatient service (PR = 1.45; 95% CI: [1.08, 1.94]; p = 0.014), infant welfare (PR = 0.43; 95% CI: [0.28, 0.66]; p < 0.001), immunization (PR = 0.56; 95% CI: [0.45, 0.70]; p < 0.001), and PMTCT (PR = 0.41; 95% CI: [0.37, 0.46]; p < 0.001) were associated with HIV transmission. After adjusting for other covariates, only PMTCT was associated with transmission (aPR = 0.66; 95% CI: [0.51, 0.86]; p = 0.002). CONCLUSIONS: While PMTCT accounts for most tested children, high HIV positivity rates were found among children presenting at inpatient, nutrition, and outpatient services and HIV care units. Thus, systematic HIV testing should be proposed for all sick children presenting at the hospital who have escaped the PMTCT cascade.

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data.

Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts in Northeast Thailand, with each exhibiting a varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran's I, and the relationship between the melioidosis morbidity rate and the environmental indicators was evaluated using a geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

Segmentation of stunting, wasting, and underweight in Southeast Sulawesi using geographically weighted multivariate Poisson regression.

The health profile of Southeast Sulawesi Province in 2021 shows that the prevalence of stunting is 11.69 %, wasting 5.89 % and underweight 7.67 %. This relatively high figure should be immediately reduced to zero because it greatly affects the quality of human resources. Cases of stunting, wasting and underweight are an iceberg phenomenon, especially in Southeast Sulawesi. Therefore, it is necessary to research the number of cases of stunting, wasting and underweight in Southeast Sulawesi using GWMPR. The research results show that there is a trivariate correlation between the number of cases of stunting, wasting and underweight. The GWMPR model provides better results in modeling the number of stunting, wasting and underweight cases than the MPR model. The models produced for each sub-district are different from each other based on the predictor variables that have a significant effect and the estimated parameter values ​​for each sub-district. The segmentation of the number of stunting cases consists of 21 regional groups with 10 significant predictor variables, while the number of wasting cases consists of 10 regional groups with 9 significant predictor variables, while the number of underweight cases consists of 37 regional groups with 11 significant predictor variables. Therefore, policies on stunting, wasting, and underweight should be based on local conditions. 3 important components of this study: 1. GWMPR is the development of GWPR model when there are 2 or more response variables that are correlated. 2. GWMPR is a spatial model that considers geography. 3. Application of GWMPR to the analysis of the number of stunting, wasting, and underweight in Southeast Sulawesi province.

Goodness-of-fit tests for modified Poisson regression possibly producing fitted values exceeding one in binary outcome analysis.

Modified Poisson regression, which estimates the regression parameters in the log-binomial regression model using the Poisson quasi-likelihood estimating equation and robust variance, is a useful tool for estimating the adjusted risk and prevalence ratio in binary outcome analysis. Although several goodness-of-fit tests have been developed for other binary regressions, few goodness-of-fit tests are available for modified Poisson regression. In this study, we proposed several goodness-of-fit tests for modified Poisson regression, including the modified Hosmer-Lemeshow test with empirical variance, Tsiatis test, normalized Pearson chi-square tests with binomial variance and Poisson variance, and normalized residual sum of squares test. The original Hosmer-Lemeshow test and normalized Pearson chi-square test with binomial variance are inappropriate for the modified Poisson regression, which can produce a fitted value exceeding 1 owing to the unconstrained parameter space. A simulation study revealed that the normalized residual sum of squares test performed well regarding the type I error probability and the power for a wrong link function. We applied the proposed goodness-of-fit tests to the analysis of cross-sectional data of patients with cancer. We recommend the normalized residual sum of squares test as a goodness-of-fit test in the modified Poisson regression.

Probabilistic forecasting of hourly emergency department arrivals.

An accurate forecast of Emergency Department (ED) arrivals by an hour of the day is critical to meet patients' demand. It enables planners to match ED staff to the number of arrivals, redeploy staff, and reconfigure units. In this study, we develop a model based on Generalised Additive Models and an advanced dynamic model based on exponential smoothing to generate an hourly probabilistic forecast of ED arrivals for a prediction window of 48 hours. We compare the forecast accuracy of these models against appropriate benchmarks, including TBATS, Poisson Regression, Prophet, and simple empirical distribution. We use Root Mean Squared Error to examine the point forecast accuracy and assess the forecast distribution accuracy using Quantile Bias, PinBall Score and Pinball Skill Score. Our results indicate that the proposed models outperform their benchmarks. Our developed models can also be generalised to other services, such as hospitals, ambulances or clinical desk services.

Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia.

Exposure to particulate matter (PM) pollution is a significant health risk, driving the search for innovative metrics that more accurately reflect the potential harm to human health. Among these, oxidative potential (OP) has emerged as a promising health-based metric, yet its application and relevance across different environments remain to be further explored. This study, set in two high-altitude Bolivian cities, aims to identify the most significant sources of PM-induced oxidation in the lungs and assess the utility of OP in assessing PM health impacts. Utilizing two distinct assays, OPDTT and OPDCFH, we measured the OP of PM samples, while also examining the associations between PM mass, OP, and black carbon (BC) concentrations with hospital visits for acute respiratory infections (ARI) and pneumonia over a range of exposure lags (0-2 weeks) using a Poisson regression model adjusted for meteorological conditions. The analysis also leveraged Positive Matrix Factorization (PMF) to link these health outcomes to specific PM sources, building on a prior source apportionment study utilizing the same dataset. Our findings highlight anthropogenic combustion, particularly from traffic and biomass burning, as the primary contributors to OP in these urban sites. Significant correlations were observed between both OPDTT and PM2.5 concentration exposure and ARI hospital visits, alongside a notable association with pneumonia cases and OPDTT levels. Furthermore, PMF analysis demonstrated a clear link between traffic-related pollution and increased hospital admissions for respiratory issues, affirming the health impact of these sources. These results underscore the potential of OPDTT as a valuable metric for assessing the health risks associated with acute PM exposure, showcasing its broader application in environmental health studies.

Home Advantage and Away Disadvantage of Teams in Champions League: Is It Valid for All Teams and Against Every Opponent?

The home advantage (HA) is a robust phenomenon in soccer whereby the home team wins more games and scores more goals than the away team. Similarly, away disadvantage (AD) means that an away team loses more games or scores less goals than the home team. This study examines the HA and AD values of teams in the UEFA-Champions League, covering the seasons from 2003/2004 to 2021/2022, a total of 2,344 matches. Controlling for team ability differences, the study revealed significant variations in HA, ranging from 32.1% to 79.5%, while AD values ranged from 45.1% to 71.9%. The study further found that HA remained consistent for teams across both the group and knockout stages, while AD varied between these stages. Furthermore, the results suggest that, for certain teams, HA is predominantly manifested against weaker opponents, and the impact of opponent strength on HA and AD is limited.

Geographically weighted regression analysis to assess hotspots of early sexual initiation and associated factors in Ethiopia.

Background: Early sexual initiation (ESI) causes unintended pregnancy, sexually transmitted infections (STI), high risk of depression and anxiety, developmental delays, lack of emotional maturity, and difficulty in pursuing education. This study aims to analyze the geographically weighted regression and associated factors of ESI of women in Ethiopia. Methods: The study utilized data from the Ethiopian Demographic and Health Survey, 2016. It included a weighted sample of 11,775 women. Spatial regression was carried out to determine which factors are related to hotspots of ESI of women. To identify the factors associated with ESI, a multilevel Poisson regression model with robust variance was conducted. An adjusted prevalence ratio (APR) with its 95 % confidence interval was presented. Results: The prevalence of ESI was 75.3 % (95%CI: 74.6 %, 76.1 %), showing notable spatial variation across different regions of Ethiopia. Areas of significant hotspots of ESI were identified in Western and Southern Tigray, most parts of Amhara, Southern, Central and Western Afar, Eastern Gambella, and North Western SNNPR. The significant variables for the spatial variation of ESI were; being single, rural residence, and having no formal education of the women. Factors including; wealth index, marital status, khat chewing, education level, residence, and region were associated significantly with ESI in the multilevel robust Poisson analysis. Conclusion: A higher proportion of ESI in women was found. Public health interventions must be made by targeting hotspot areas of ESI through increasing health care access and education (specifically among rural residents), developing a comprehensive sexual education, implementing policies and laws that outlaw early marriage, and mass community-based programs to increase awareness about the importance of delaying sexual activity.

Flexible model-based non-negative matrix factorization with application to mutational signatures.

Somatic mutations in cancer can be viewed as a mixture distribution of several mutational signatures, which can be inferred using non-negative matrix factorization (NMF). Mutational signatures have previously been parametrized using either simple mono-nucleotide interaction models or general tri-nucleotide interaction models. We describe a flexible and novel framework for identifying biologically plausible parametrizations of mutational signatures, and in particular for estimating di-nucleotide interaction models. Our novel estimation procedure is based on the expectation-maximization (EM) algorithm and regression in the log-linear quasi-Poisson model. We show that di-nucleotide interaction signatures are statistically stable and sufficiently complex to fit the mutational patterns. Di-nucleotide interaction signatures often strike the right balance between appropriately fitting the data and avoiding over-fitting. They provide a better fit to data and are biologically more plausible than mono-nucleotide interaction signatures, and the parametrization is more stable than the parameter-rich tri-nucleotide interaction signatures. We illustrate our framework in a large simulation study where we compare to state of the art methods, and show results for three data sets of somatic mutation counts from patients with cancer in the breast, Liver and urinary tract.

Factors associated with the use of antibiotics for children presenting with illnesses with fever and cough obtained from prescription and non-prescription sources: a cross-sectional study of data for 37 sub-Saharan African countries.

INTRODUCTION: Fever and cough in under-five children are common and predominately self-limiting illnesses. Inappropriate prescribing of antibiotics in sub-Saharan Africa is a significant public health concern. However, prescription sources and use among children with fever or cough have not been explored. Therefore, we explored the factors associated with the use of antibiotics obtained from prescription and non-prescription sources for children with illnesses associated with fever and cough. METHODS: A secondary data analysis was conducted based on the Demographic and Health Survey (DHS) data from 37 sub-Saharan African countries. A total weighted sample of 18,866 under-five children who had a fever/cough and took antibiotics were considered for this study. Given the hierarchical nature of DHS data and the use of antibiotics prescribed from the formal healthcare setting (> 10%), a multilevel modified poisson regression model was fitted. Deviance was used for model comparison and the model with the lowest deviance value was chosen as the best-fitted model. Variables with p ≤ 0.2 in the bivariable analysis were considered for the multivariable modified poisson regression model. In the multivariable multilevel modified poisson regression model, the Adjusted Prevalence Odds Ratio (APOR) with a 95% Confidence Interval (CI) and p-value < 0.05 were reported to declare a significant association with taking antibiotics for fever/cough prescribed from formal healthcare setting. RESULTS: In sub-Saharan Africa, the proportion of use of antibiotics from informal healthcare setting for fever and cough among under-five children was 67.19% (95% CI: 66.51%, 67.85%). In the multilevel modified poisson regression analysis; residing in a rural area (APOR = 1.08, 95% CI: 1.04, 1.12), a child aged 36-47 months (APOR = 0.94, 95% CI: 0.90, 0.98), a child aged 48-59 months (APOR = 0.89, 95% CI: 0.84, 0.94), maternal primary education (APOR = 0.96, 95% CI: 0.93, 0.99), maternal secondary education (APOR = 0.95, 95% CI: 0.92, 0.99), belonged the middle household wealth status (APOR = 1.07, 95% CI: 1.02, 1.11), maternal exposure to news/electronic media (APR = 1.06, 95% CI: 1.02, 1.10), being from a household with 2 under-five children (APR = 0.94, 95% CI: 0.91, 0.97), being from a household with 3 under-five children (APR = 0.89, 95% CI: 0.85, 0.93), being from a household with 4 under-five children (APR = 0.90, 95% CI: 0.83, 0.98), and children of caregivers who were not involved in decision-making for their child health issues were significantly associated with taking antibiotics prescribed from formal healthcare setting for fever/cough among under-five children. CONCLUSION: Only two-thirds of the antibiotics used for children under five who had fever and cough were prescribed from formal healthcare setting. Our findings underscore the significance of addressing healthcare disparities, improving access to qualified healthcare providers, promoting maternal education, and empowering mothers in healthcare decision-making to ensure appropriate antibiotic use in this vulnerable population. Further research and interventions targeted at these factors are warranted to optimize antibiotic prescribing practices and promote responsible antibiotic use in the management of fever and cough in under-five children.

Changing trends in Japanese spotted fever epidemiology in Shimane, Japan: A two-decade retrospective study with emphasis on the COVID-19 pandemic era.

INTRODUCTION: The objective of this study is to evaluate the epidemiological characteristics of Japanese Spotted Fever (JSF) cases reported through the National Epidemiological Surveillance of Infectious Disease (NESID) system in Shimane Prefecture, Japan, from 2000 to 2022, encompassing the periods before and during the COVID-19 pandemic period. METHODS: A retrospective analysis was conducted on JSF cases reported to the NESID system in Shimane Prefecture between 2000 and 2022. Population data were obtained from the Statistical Information of Shimane. Poisson regression analysis was employed to examine the relationship between the annual prevalence rate of JSF and the COVID-19 pandemic. RESULTS: A total of 301 JSF cases were analyzed during the study period. Even the pre-COVID-19 pandemic period, a gradual and significant increase in the prevalence rate was observed (prevalence rate = 1.03, 95% CI: 1.01-1.05; p = 0.01), and a rapid increase was noted since 2020 (prevalence rate = 1.57, 95% CI: 1.39-1.78; p < 0.01). The slope during the pre-COVID-19 pandemic period was estimated to have significantly increased (p < 0.01). CONCLUSIONS: Our findings suggest that while the prevalence rate of JSF had exhibited a slight increase in the years preceding the COVID-19 pandemic, it demonstrated a more significant increase following the pandemic in Shimane Prefecture. JSF has increased since 2020 and may be linked to COVID-19 pandemic. The COVID-19 pandemic has had a substantial impact on global health, underscoring the importance of investigating the prevalence of specific infectious diseases and other health-related indicators to accurately assess the pandemic's impact.

Sociodemographic factors underlying lifetime fertility among ever-married Swazi women.

Fertility rates remain high in certain subgroups of the population, and there is limited research about the sociodemographic factors influencing fertility, particularly in Eswatini where women are often considered minors. This study aims to investigate the changes in lifetime fertility, and the associations between sociodemographic factors and lifetime fertility among ever-married women. The study used secondary cross-sectional data from the 2010 and 2014 Eswatini Multiple Indicator Cluster Surveys (MICS), with a sample size of 2,295 and 2,351 women, respectively. The data was analysed using descriptive statistics and multivariable Poisson regression. The results showed that fertility rates decreased from 3.47 to 3.21 children between 2010 and 2014. The study found that child loss and age (25+ years) were significant factors associated with higher fertility, while delayed age at marriage and sexual debut (20+ years), at least secondary education, and being rich were strong predictors of lower fertility rates. The study recommends creating awareness about and strengthening laws to abolish early sexual debut and marriage. It also suggests empowering women through education, encouraging the use of contraceptives, and providing maternal and child health services in rural areas where fertility rates tend to be higher.

Les taux de fécondité restent élevés dans certains sous-groupes de la population, et les recherches sur les facteurs sociodémographiques influençant la fécondité sont limitées, en particulier à Eswatini où les femmes sont souvent considérées comme mineures. Cette étude vise à étudier les changements dans la fécondité au cours de la vie et les associations entre les facteurs sociodémographiques et la fécondité au cours de la vie chez les femmes déjà mariées. L'étude a utilisé des données transversales secondaires des enquêtes par grappes à indicateurs multiples (MICS) d'Eswatini de 2010 et 2014, avec un échantillon de 2 295 et 2 351 femmes, respectivement. Les données ont été analysées à l'aide de statistiques descriptives et d'une régression de Poisson multivariée. Les résultats ont montré que les taux de fécondité ont diminué de 3,47 à 3,21 enfants entre 2010 et 2014. L'étude a révélé que la perte d'enfants et l'âge (25 ans et plus) étaient des facteurs importants associés à une fécondité plus élevée, tandis qu'un âge plus tardif au mariage et aux débuts sexuels (20 ans et plus) ), au moins une éducation secondaire, et le fait d'être riche étaient de puissants prédicteurs de taux de fécondité plus faibles. L'étude recommande de sensibiliser et de renforcer les lois visant à abolir les premiers rapports sexuels et le mariage précoces. Il suggère également d'autonomiser les femmes grâce à l'éducation, d'encourager l'utilisation de contraceptifs et de fournir des services de santé maternelle et infantile dans les zones rurales où les taux de fécondité ont tendance à être plus élevés.

The effects of health risk behaviors to excess mortality in the population with depression: A cohort study based on NHANES data.

BACKGROUND: The population with depression had a considerable excess mortality risk. This increased mortality may be attributed to the biological consequences of depression or the substantial prevalence of health risk behaviors (HRBs). This study aimed to quantify the combined effects of four major HRBs - smoking, excessive alcohol use, physical inactivity, and an unhealthy diet - on excess mortality among depressed individuals. METHODS: This study included 35,738 adults from the National Health and Nutrition Examination Survey 2005-06 to 2017-18, with mortality follow-up data censored through 2019. The standardized prevalence of HRBs was calculated for populations with and without depression. Poisson regression models were used to calculate the mortality rate ratio (MRR). Based on model adjusting for socio-demographic factors, the attenuation of MRR was determined after further adjustment for HRBs. RESULTS: A total of 3147 participants were identified as having depression. All HRBs showed a significantly higher prevalence among the population with depression. After adjusting for socio-demographic factors, depression was associated with 1.7 and 1.8 times higher all-cause and cardiovascular disease mortality rate, respectively. Further adjustment for all current HRBs resulted in a 21.9 % reduction in all-cause mortality rate and a 15.4 % decrease in cardiovascular disease mortality rate. LIMITATION: HRBs were reported at a single time point, and we are unable to demonstrate a causal effect. CONCLUSION: At least 1/5 of excess mortality for population with depression was attributable to HRBs. Efforts should be made to address HRBs among population with depression.

Geo-spatial epidemiology of gallbladder cancer in Bihar, India.

Recently, a substantial increase in gallbladder cancer (GBC) cases has been reported in Bihar, India. The region's groundwater can naturally contain harmful concentrations of arsenic, which appears to be epidemiologically linked to the unusually high incidence. However, the root causes remain largely unexplored. Recent findings of uranium in the state's groundwater may also have associations. This study investigates the geo-spatial epidemiology of GBC in Bihar, India-with a focus on the correlation between environmental carcinogens, particularly arsenic and uranium in groundwater, and the incidence of GBC. Utilizing data from 8460 GBC patients' registration records over an 11-year period at a single health center, the research employs Semi-parametric Geographically Weighted Poisson Regression (S-GWPR) to account for non-stationarity associations and explores significant factors contributing to GBC prevalence at a subdistrict level. The S-GWPR model outperformed the standard Poisson regression model. The estimates suggest that arsenic and uranium concentrations in groundwater did not present significant associations; however, this could be due to the lower resolution of this data at the district level, necessitating higher resolution data for accurate estimates. Other socio-environmental factors included demonstrated significant regional heterogeneity in their association with GBC prevalence. Notably, each 1 % increase in the coverage of well- and canal-irrigated areas is associated with a maximum of 3.0 % and 5.2 % rise in the GBC incidence rate, respectively, likely attributable to carcinogen exposure from irrigation water. Moreover, distance to the health center and domestic electricity connections appear to influence the number of reported GBC cases. The latter suggests that access to electricity might have facilitated the use of groundwater pumps-increasing exposure to carcinogens. The results underscore the necessity for targeted health policies and interventions based on fine-resolution spatial analysis, as well as ongoing environmental monitoring and research to better understand the multifaceted risk factors contributing to GBC.

Estimated Incidence of Hospitalizations and Deaths Attributable to Respiratory Syncytial Virus Infections Among Adults in Germany Between 2015 and 2019.

INTRODUCTION: Respiratory syncytial virus (RSV) burden in adults is underestimated mainly due to unspecific symptoms and limited standard-of-care testing. We estimated the population-based incidence of hospitalization and mortality attributable to RSV among adults with and without risk factors in Germany. METHODS: Weekly counts of hospitalizations and deaths for respiratory, cardiovascular, and cardiorespiratory diseases were obtained (Statutory Health Insurance database, 2015-2019). A quasi-Poisson regression model was fitted to estimate the number of hospitalizations and deaths attributable to RSV as a function of periodic and aperiodic time trends, and viral activity while allowing for potential overdispersion. Weekly counts of RSV and influenza hospitalizations in children < 2 years and adults ≥ 60 years, respectively, were used as viral activity indicators. Models were stratified by age group and risk status (defined as presence of selected comorbidities). RESULTS: Population-based RSV-attributable hospitalization incidence rates were high among adults ≥ 60 years: respiratory hospitalizations (236-363 per 100,000 person-years) and cardiorespiratory hospitalizations (584-912 per 100,000 person-years). RSV accounted for 2-3% of all cardiorespiratory hospitalizations in this age group. The increase in cardiorespiratory hospitalization risk associated with underlying risk factors was greater in 18-44 year old persons (five to sixfold higher) than in ≥ 75 year old persons (two to threefold higher). CONCLUSIONS: This is a first model-based study to comprehensively assess adult RSV burden in Germany. Estimated cardiorespiratory RSV hospitalization rates increased with age and were substantially higher in people with risk factors compared to those without risk factors. Our study indicates that RSV, like other respiratory viruses, contributes to both respiratory and cardiovascular hospitalizations. Effective prevention strategies are needed, especially among older adults ≥ 60 years and among adults with underlying risk factors.

Regional disparities in antenatal care utilization among pregnant women and its determinants in Ethiopia.

Background: Antenatal care primarily focuses on health care checkups, the provision of advice on healthy behaviors, and the delivery of psychological, social, and emotional support for women with pregnancy. The national target set by the Ethiopian government is to achieve 95% of at least four ANC visits. Nevertheless, 43.11% of women had four or more checkups, according to the 2019 Ethiopian Demographic and Health Survey. Despite this achievement, antenatal care visits differ significantly between Ethiopian regions. Consequently, the purpose of this study was to assess regional disparities in pregnant women's utilization of antenatal care and its determinants in Ethiopia. Methods: We have used 2019 intermediate Ethiopian Demographic and Health Survey data for analysis. The analysis comprised a total of 3,917 weighted women age 15-49 who had a live birth in the 5 years preceding the survey. Poisson regression analysis was done using SAS software version 9.4. To show the strength and direction of the association, an incidence rate ratio with a 95% confidence interval was used. Variables with a p-value <0.05 were declared as significant factors associated with the number of ANC visits. Results: In Ethiopia, the number of ANC visits differs between regions. With a mean of 4.74 (95% CI: 4.49, 4.99), Addis Ababa reported the highest percentage of ANC visits (82.7%), while the Somali Region reported the lowest percentage (11.3%) with a mean of 0.73 (95% CI: 0.57, 0.88). Maternal age, educational level, religion, household wealth index, place of delivery, and household size show significant associations with the number of antenatal care visits. Conclusions: In Ethiopia, there is the highest regional disparity in the number of ANC visits. The number of ANC visits was influenced by the mother's age, education, religion, household wealth index, place of delivery, and household size. Regarding the ANC visits, there should be initiatives that address the demands of pastoralist and agro-pastoralist communities to increase ANC utilization. As with many other health outcomes, education and low socio-economic status were associated with low ANC visit but these are tied to the overall social development of a country and are not immediately amenable to public health interventions.