Rural Residents Research Articles

Abstract 3610: Healthcare segregation experienced by colorectal cancer patients residing in high-poverty areas and its impact on health outcomes

Background: Existing evidence indicates that colorectal cancer (CRC) patients from high-poverty areas (HPA), defined as areas with 20% or more residents living below federal poverty level, are more likely to receive surgery at low-volume, non-accredited hospitals than those from low-poverty areas (LPA). The systematic difference in surgical care location between patients from HPAs and LPAs, healthcare segregation, could represent a structural equity through which disparities in health outcomes arise. We sought to determine the existence of healthcare segregation and assess its impact on patient health outcomes. Methods: We identified patients undergoing surgery for non-metastatic CRC diagnosed in 2009-2019 from SEER-Medicare. Patients living in a county which had been an HPA for at least 30 years were classified as living in a persistent-poverty area (PPA). Patients living in a county which was an HPA during the year of cancer diagnosis but not a PPA were classified as living in a current-poverty area (CPA). Otherwise, they were classified as living in an LPA. Experiencing healthcare segregation was defined as being treated at a poverty-area-serving (PAS) hospital where ≥50% of the patients were from HPAs. We examined the association between area-level poverty, treatment at PAS hospitals, and health outcomes (postoperative adverse events, 30-day readmission, long-term all-cause mortality (ACM), and cancer-specific mortality (CSM)) using logistic and Cox regression. We performed a subgroup analysis for metropolitan, urban, and rural areas. Results: We included 81,767 patients (7.5% from PPAs, 8.4% from CPAs) with a median age of 78 (IQR: 73-84) years. 53.9% of patients were females, 14% were non-White, and 1.5% lived in rural areas. 81% of the hospitals (180/991) were PAS hospitals, which treated 64% of patients from PPAs and CPAs vs. 3% from LPAs. Compared with patients from LPAs treated at non-PAS hospitals, those treated at PAS hospitals who were from PPAs (ACM HR=1.17(1.08-1.26), CSM HR=1.23(1.11-1.37)) and CPAs (ACM HR=1.15(1.08-1.22), CSM HR=1.23(1.13-1.35)) had worse short and long-term outcomes. Patients from CPAs treated at non-PAS hospitals also had worse outcomes, to a lesser degree (ACM HR=1.12(1.05-1.19), CSM HR=1.16(1.06-1.28)). Among rural residents, being treated at PAS-serving hospitals but not area-level poverty was independently associated with worse outcomes. Conclusions: Patients living in HPAs experience healthcare segregation in CRC treatment, contributing to their worse health outcomes. Healthcare segregation reflects systemic inequities and structural barriers limiting access to resources that patients from HPAs may deploy to mitigate consequences of cancer. Understanding healthcare segregation and factors shaping it can help identify areas for intervention to reduce associated health disparities. Citation Format: Xinyan Zheng, Laura C. Pinheiro, Parisa Tehranifar, Erica Phillips, Rulla M. Tamimi, Steven Y. Chao, Maria Pisu, Chuxuan Gao, Andrew G. Rundle, Jialin Mao. Healthcare segregation experienced by colorectal cancer patients residing in high-poverty areas and its impact on health outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3610.

Examining Child Labour Activities in South Africa

Abstract Background South Africa is a developing country characterised by high unemployment, poverty and inequality. Thus, it is possible child members of households are exploited to help the households survive financially. Objective This study investigated child labour activities in South Africa, and examined the impact of various personal- and household-level factors (including labour market status of adult members) on child labour incidence. Methods Data from the Survey of Activities of Young People (SAYP) released by Statistics South Africa was analysed to derive descriptive statistics relating to child labour activities. Probit regressions were also conducted to investigate the impact of various factors on child labour probability. Results Children involved in child labour were predominantly African rural residents who did not attend schools at the time of the survey, and came from households with only one employed adult member on average. These children spent four to five hours per week on economic activities in unskilled elementary occupations, and the key reasons for involving in these activities were to earn pocket money for themselves and assist their families. Regarding the results of probit regressions, children coming from households with a greater number of employed adult members were less likely to be in child labour, but the result was only statistically significant in 2015. Conclusions Child labour does exist in South Africa, particularly amongst households with a low number of employed adult members. Numerous socio-economic problems (such as poverty and adult unemployment) would need to be addressed to fully eradicate child labour incidence.

Frequency of Third-Degree Atrioventricular Block in Inferior Wall Myocardial Infarction with Right Ventricular Infarction

Background: Complete atrioventricular block is a significant complication in inferior wall myocardial infarction and right ventricular infarction patients. Understanding its prevalence and demographic determinants are essential in order to optimize the clinical management and the evaluation of prognosis, most significantly in low-resource health systems. Objective: To determine the frequency of third-degree atrioventricular block with right ventricular infarction in a patient with acute inferior wall myocardial infarction. Study Design: Cross-sectional study. Duration and Place of Study: The study was conducted from September 2024 to February 2025 at the Cardiology Unit and Emergency Department of Ayub Teaching Hospital, Abbottabad. Methodology: A total of 110 patients aged 35–85 years, diagnosed with IWMI and RVI, were included. Diagnosis was based on clinical symptoms, electrocardiographic findings, and cardiac biomarkers. Third-degree AV block was identified through conventional 12-lead ECG, and right ventricular infarction was confirmed using right-sided precordial leads. Results: The mean age of patients was 63.29 ± 8.96 years, with a predominance of male patients (76.4%). Third-degree AV block occurred in 20.9% of patients, with a significant gender difference (73.1% of females vs. 4.8% of males, p<0.001). Rural residents had a higher incidence (39%) of AV block compared to urban residents (0%, p<0.001). Conclusion: The study confirms a significant frequency of third-degree AV block in patients with IWMI and RVI, with a marked predisposition in females, rural residents, and individuals from low socioeconomic backgrounds.

Adaptation Analysis of Urban Village Resettlers Based on Lefebvre’s Spatial Production Theory in Qingdao, China

The demolition and resettlement of urban villages is a new urbanization strategy widely used by the Chinese government. It is a massive development intervention designed and implemented by the Chinese government to promote the relocation and resettlement of the rural-to-urban population. However, limited research has focused on how rural residents adapt to their new urban lives within these large-scale relocation and resettlement projects. This paper aims to analyze this adaptation process. This study employs Lefebvre’s spatial production theory, based on a survey of 256 resettled residents in Qingdao, China, using a structured questionnaire and the statistical analysis software SPSS 24.0 to quantitatively evaluate the adaptability of resettled residents based on three dimensions: material space, institutional space, and social space. Descriptive statistics and correlation analyses are conducted to explore the relationships among these dimensions. Our findings reveal an association between high adaptation levels and urban resident identity recognition among the resettled residents. Our research findings raise more substantial concerns about the transparency of government decision-making and the community participation of resettlers in the current resettlement process.

Determinants of contraceptive use prior to onset of childbearing among ever-married women in Indonesia: a secondary data analysis

BackgroundDespite high rates of early marriage and adolescent childbearing in Indonesia—which increase risks for both maternal and child health—family planning efforts largely focus on birth spacing or limiting the number of children. Few programs specifically address the reproductive needs of ever-married women who wish to prevent or delay their first birth. This study investigates the sociodemographic factors influencing contraceptive use prior to childbearing among ever-married women in Indonesia.MethodsWe analyzed weighted data from 121,916 ever-married women using the 2002–2017 Indonesia Demographic and Health Surveys. Variables were selected based on prior research and bivariate screening. Univariate and multiple survey logistic regression analyses were performed; model selection was guided by the Akaike Information Criterion, and Nagelkerke R-square quantified the explained variance.ResultsOverall, 4.66% of ever-married women reported using contraception before having any children. Younger women (15–19 years), those preferring a smaller family size, being employed, and residing in Java were significantly associated with higher usage. Contrary to conventional assumptions, the poorest wealth quintile had notably high odds of pre-childbearing contraceptive use, second only to the richest. Interactions involving education and rural residence highlighted the multifaceted nature of these reproductive decisions.DiscussionThese findings underscore the need for targeted policies to address diverse socioeconomic barriers and to empower women who wish to delay their first birth.

Senility, defecation disorders, sleep disorders, and non-operative spinal infections: A single-center retrospective analysis

BACKGROUND Non-operative spinal infections (NOSI) are caused by tuberculosis, brucella, and other specific bacteria. The etiology of the disease is insidious, the onset is slow and the diagnosis and treatment are difficult. Identifying the factors associated with spinal infection and early intervention can reduce the occurrence of the disease. At present, the research mainly focuses on the accurate diagnosis and treatment of spinal infection, and there are few studies on the prevention of spinal infection. The concept of "preventive treatment of diseases" in traditional Chinese medicine may help identify the causes and reduce the occurrence of NOSI. AIM To determine the association of age, bowel movements, and sleep patterns with NOSI. METHODS Data of 69 NOSI patients and 84 healthy controls in a tertiary hospital from January 2019 to June 2024 were collected. Patients with NOSI had imaging evidence (magnetic resonance imaging) of spinal infections (including infections caused by tuberculosis, brucopathy, and other pathogens) and had no history of spinal surgery in the last 1 year were included in the analysis. Patients with spinal infection due to spinal surgery are excluded in the study. Data including age, sex, place of residence, sleeping status, and bowel movements were collected. SPSS22.0 was used for correlation analysis of all data. RESULTS The mean age of the NOSI group and the control group was 63.55 ± 14.635 years and 59.18 ± 17.111 years, respectively, without statistical difference (P = 0.096). There was also no statistically significant difference in gender between the two groups. In the NOSI group, 45 (65.22%) were over 60 years old, and 44 (63.77%) were rural residents. Compared with the control group, the NOSI group had more patients with sleep disorder and defecation disorder, accounting for 69.57% and 68.12%, respectively, with significant statistical difference (both P < 0.001). Regression analysis showed that defecation and sleep disorders were closely related to NOSI (both P < 0.001). CONCLUSION Most patients with NOSI are older and have sleep disorders and abnormal defecation.

Diverging cognitive benefits from education between rural and urban middle-aged and older adults in the USA.

Subjective cognitive decline (SCD) is defined as self-reported increase in confusion or memory loss. There is limited research on the interplay between rural-urban residence and education on SCD. Examine rural-urban differences in SCD, and whether education moderates this relationship. Respondents aged ≥45 years were queried about SCD in the 2022 Behavioral Risk Factor Surveillance System data, creating a sample size of 63 890. A logistic regression analysed the association between rural-urban residence and SCD, and moderation was tested by an interaction with education. SCD was more common among rural (12.0%) compared with urban (10.7%) residents. Rural residence was associated with 9% significantly higher odds of SCD compared with urban residence after adjusting for sociodemographic and health covariates (adjusted odds ratio (aOR) = 1.09, P = 0.01). There was a negative relationship between education level and SCD, including the association of college degree with 15% lower odds of SCD compared with less than high school degree (aOR = 0.85, P < 0.01). Education was a significant moderator, with higher education associated with lower odds of SCD for urban, but not rural, residents. Rural setting and lower education were associated with higher odds of SCD, but higher education was protective for only urban residents. These results indicate that higher education may be a gateway for more opportunities and resources in urban settings, with cascading impacts on cognition. Future research should examine reasons for the diverging cognitive benefits from education depending on rural-urban residence.

Propensity Score Matching Analysis of the Association between Instructor Competence and Utilization of Digital Tools in TVET Institutions of Uganda

The effectiveness of online teaching in Technical and Vocational Education and Training (TVET) institutions largely depends on instructor competence in utilizing digital gadgets. This paper utilizes the Propensity Score Matching model to examine the association between instructor digital gadgets utilization competence and online teaching/learning among selected TVET institutions. This paper presents and emphasizes the critical role of digital competence among instructors as a necessary condition for online teaching. A cross-sectional survey design was employed. Univariate analysis using bar charts and histograms was done. The bivariate analysis covered an ANOVA table and scatterplot, while the Multivariate level entailed the Propensity Score Matching model. The findings showed that instructor competence in digital gadget utilization enhances online teaching, but rural residences and poor infrastructure limit engagement. Internet access remains a major hindrance, requiring government intervention for free connectivity. Practical fields face significant challenges in integrating online teaching, necessitating hefty investments in digital learning tools and simulators. Financial constraints among instructors, due to limited income-generating activities, further reduce online teaching adoption in TVET institutions

Uptake of the recently introduced vaccines among children aged 12–23 months in Ethiopia: a multilevel analysis of the 2019 Ethiopia Mini Demographic and Health Survey

ObjectiveThough vaccination coverage in Ethiopia has shown steady progress over the years, there are districts with below targeted vaccination coverage. This study assessed the magnitude and determinants of recently introduced...

GEOGRAPHIC INEQUITIES AND ACCESS TO COLORECTAL CANCER SURGERY AMONG RURAL RESIDENTS: ONE SIZE DOES NOT FIT ALL!

GEOGRAPHIC INEQUITIES AND ACCESS TO COLORECTAL CANCER SURGERY AMONG RURAL RESIDENTS: ONE SIZE DOES NOT FIT ALL!

Determinants of the use of insecticide-treated nets and intermittent preventive treatment of malaria among pregnant women in Angola.

The determinants of insecticide-treated nets (ITNs) use and uptake of three doses or more of intermittent preventive treatment with sulfadoxine-pyrimethamine (IPTp 3+) among pregnant women can vary between regions and is not well studied in Angola. This study analysed secondary data of a cluster-randomized controlled trial that evaluated the impact of the Maternal and Child Health Handbook (MCH-HB) on the continuum of care among pregnant women and mothers in Angola from 2019 to 2020. Those who received antenatal care (ANC) were analysed. Multivariable logistic regression analyses were performed to assess factors associated with ITN use and IPTp 3+ uptake. Among 8336 participants, 62.7% used ITNs and 48.7% achieved IPTp 3+. Only 31.7% achieved both. Single women were less likely to use ITNs. Women who completed secondary education, were wealthier and achieved IPTp 3+ were more likely to use ITNs. Teenagers, multiparous mothers, rural area residents and those who attended ANC later were less likely to achieve IPTp 3+. Those who completed secondary education, were wealthier, had longer travel times to health facilities and were in the MCH-HB group were more likely to achieve IPTp 3+. The identified risk groups can be targeted for interventions to improve coverage.

Behavioral Response Analysis of Rural Residents’ Living Waste Classification: Evidence from Jiangsu, China

Maximizing rural residents’ primary role in domestic waste sorting and management is critical to improving the rural living environment and advancing socioeconomic development. This study aims to analyze the entire process of domestic waste sorting by rural residents using sample data from 2420 rural households surveyed in the 2021 China Land Economic Survey (CLES). Based on the Theory of Planned Behavior (TPB), this study develops a research framework for analyzing the entire process of rural residents’ domestic waste-sorting behavior. It examines the inter-relationships among behavioral cognition, behavioral intention, and behavioral response and employs structural equation modeling (SEM) for empirical verification. The results demonstrate that subjective norms, classification attitudes, and perceived behavioral control exert statistically significant positive effects on both rural residents’ intention and behavioral responses toward domestic waste sorting. Moreover, sorting intention demonstrates a significant predictive effect on actual sorting behavior. This study further identifies a mediating role of sorting intention throughout the behavioral process, while potential correlations among subjective norm, behavioral attitude, and perceived behavioral control suggest additional mechanisms underlying rural residents’ waste-sorting responses that warrant further exploration.

Oesophageal cancer-specific mortality risk and public health insurance: Prospective cohort study from China.

Oesophageal cancer is a significant health concern worldwide, with high incidence and mortality rates. In China, the disease burden is particularly high, accounting for a substantial proportion of oesophageal cancer cases and related deaths worldwide. To explore the relationship between the mortality rate of oesophageal cancer patients and insurance type, out-of-pocket ratio, and the joint effects of insurance type and out-of-pocket ratio. The χ 2 test was used to analyze patients' demographic and clinical characteristics. Multivariate logistic regression, the Cox proportional hazard model, and the competitive risk model were used to calculate the cumulative hazard ratios (HRs) of all-cause death and oesophageal cancer-specific death among patients with different types of insurance and out-of-pocket ratios. Compared with patients covered by basic medical insurance for urban and rural residents, patients covered by urban employee basic medical insurance for urban workers (UEBMI) had a 23.30% increased risk of oesophageal cancer-specific death [HR = 1.233, 95% confidence interval (CI): 1.093-1.391, P < 0.005]. Compared with patients in the low out-of-pocket ratio group, patients in the high out-of-pocket ratio group had a 25.80% reduction in the risk of oesophageal cancer-specific death (HR = 0.742, 95%CI: 0.6555-0.84, P < 0.005). With each 10% increase in the out-of-pocket ratio, the risk of oesophageal cancer-specific death decreased by 10.10% in patients covered by UEBMI. However, the risk of oesophageal cancer-specific death increased by 26.90% in patients in the high out-of-pocket ratio group. This study reveals the relationships of the specific mortality rate of patients with oesophageal cancer with the out-of-pocket ratio and medical insurance types as well as their combined effects. This study provides practical suggestions and guidance for the formulation of relevant policies in this area.

Using geographic information systems to map eye care service distribution in rural and remote Western Australia

BackgroundMany rural residents face barriers to eye care access. Government workforce data show a maldistribution of eye care providers in Western Australia however, no detailed information is available on regional coverage within the state. This study aimed to identify and map all eye care services in rural and remote Western Australia and to calculate the regional workforce rates.MethodsA survey was sent to all optometry and ophthalmology practices in rural and remote Western Australia with questions on practitioner and equipment availability. Information on visiting services was captured directly through organisations as well as the survey. Geographic information systems were used to map service locations, calculate coverage of services relative to the population, and calculate full-time equivalent (FTE) per 100,000 of the population for each profession.ResultsA total of 58 optometry practices, 8 ophthalmology practices, 113 visiting optometry services and 43 visiting ophthalmology services in rural and remote Western Australia were identified and mapped. Most of the population (97.2%) lived within 100 km of an eye care service. Overall FTE per 100,000 for optometry and ophthalmology were 12.1 and 2.4, respectively. Regional FTE per 100,000 ranged from 2.1 to 19.5 for optometry and 0 to 4.2 for ophthalmology.ConclusionsThe results show broad coverage of visiting services but highlights regional discrepancies in optometry and ophthalmology workforce rates, with several regions failing to meet FTE recommendations.

The Impact of Economic Financialization on the Income Gap Between Urban and Rural Residents: Evidence from China

Economic financialization refers to misappropriating workers’ earnings and enriching wealthy individuals through financial cycles. This process leads to an unequal distribution of wealth and income, particularly pronounced between urban and rural areas. This article examines the impact of economic financialization on the income gap between urban and rural residents by analyzing provincial-level data from China collected between 2003 and 2022. Utilizing the FE-SCC model and SDM, this study reveals that economic financialization increases the income gap between urban and rural residents, especially in eastern China and regions characterized by advanced economic development. The findings indicate that economic financialization significantly exacerbates the wage income gap between urban and rural residents but reduces the property income gap, which relates directly to the nature of work performed by urban and rural residents. The income disparity between these two groups correlates with each region’s economic financialization level. It is influenced by spillover effects from neighboring areas, evidenced by a phenomenon known as “club convergence”. Strengthening regulations on economic financialization, leveraging policy-driven financial systems, promoting regional development, and enhancing inclusive financial services could alleviate income disparity in urban–rural areas and improve the population’s overall well-being.

Influencing Factors of Residents’ Green Perception Under Urban–Rural Differences: A Socio-Ecological Model Approach

With the advancement of the global Sustainable Development Goals (SDGs), residents’ green perception has become a key factor in driving green behavior and the implementation of environmental policies. However, due to differences in socio-economic environments, policy enforcement, and resource accessibility between urban and rural areas, residents’ levels of green perception exhibit significant regional disparities. Based on the Social Ecological Model, this study constructs an analytical framework encompassing the individual, social relationships, community, policy, and organizational levels to systematically explore the multi-level factors influencing urban and rural residents’ green perception. This study collects data through questionnaire surveys and employs Structural Equation Modeling (SEM) to validate the relationships between variables at different levels. The findings indicate that residents’ green perception is influenced by multiple interacting factors, among which environmental knowledge and attitudes at the individual level, family support and social networks at the social relationship level, as well as community atmosphere and policy advocacy play particularly significant roles in enhancing green perception. Furthermore, there are distinct differences in the mechanisms of green perception formation between urban and rural residents; urban residents rely more on government policies and green infrastructure, whereas rural residents’ green perception is primarily influenced by community atmosphere and direct environmental experiences. This study deepens the understanding of urban–rural differences in green perception and their driving factors, providing region-specific policy recommendations to promote widespread green behavior, advance ecological civilization construction in both urban and rural areas, and facilitate the achievement of sustainable development goals.

Compositional associations of 24-h physical activities, sedentary time and sleep with depressive symptoms in urban and rural residents: a cross-sectional study

BackgroundStudies investigating the associations of 24-h movement behaviours (including moderate-to-vigorous-intensity physical activity (MVPA), light-intensity PA (LPA), sedentary time (ST) and sleep) with depressive symptoms are scarce. It is also unclear whether possible associations differ between urban and rural residents. Hence, we aimed to investigate these associations in a population-based sample of middle-aged Finnish adults.MethodsThe study population consisted of 4295 adults, aged 46 years, from the Northern Finland Birth Cohort 1966. The participants wore a hip-worn accelerometer for 14 days. Time spent in sedentary, LPA and MVPA was obtained from accelerometer data and then combined with self-reported sleep duration to obtain the 24-h composition. The residential environment was classified as urban or rural based on the participants’ home addresses. Depressive symptoms were assessed using the Beck Depression Inventory-II (BDI-II). Multivariable adjusted regression analysis using a compositional data analysis approach based on isometric log-ratio transformation was used to determine the associations between movement behaviours and depressive symptoms in urban and rural residential environments.ResultsThe 24-h movement behaviour composition was significantly associated with the BDI-II score both in urban and rural residential environment. More time spent in sleep relative to other behaviours was associated with lower BDI-II score in rural residential environments. More time spent in ST among urban residents and in LPA among rural residents was associated with higher BDI-II scores. When modelling pairwise reallocations of time, more MVPA or more sleep at the expense of LPA or ST was associated with lower BDI-II score among rural residents. For urban residents, reallocating time from ST to any other behaviour was associated with lower BDI-II score.ConclusionsOur findings showed that more relative time spent in MVPA and sleep was associated with lower levels of depressive symptoms among rural residents, and more relative time spent in any other behaviour at the expense of ST was associated with lower levels of depressive symptoms among urban residents. These differences should be considered in the prevention and treatment of depressive symptoms. Due to the cross-sectional design of this study, causality cannot be inferred, and further research exploring the mechanisms underlying these associations in diverse populations and longitudinal study settings are needed.

Construction of Depression Prediction Model Based on Machine Learning and Its Interpretability

&amp;lt;i&amp;gt;Objectives:&amp;lt;/i&amp;gt; The aim of this study was to construct depression prediction models based on machine learning algorithms, compared the performance of different machine learning models on depression risk prediction, and interpreted the model. &amp;lt;i&amp;gt;Methods:&amp;lt;/i&amp;gt; A total of 2573 participants from the CHARLS database. LASSO and stepwise regression were used to screen for variables. The dataset is randomly divided into training set, validation set and test set according to 6:2:2. SMOTE resampling was used to balance the training set when fitted the model. Nine machine learning algorithms were used to construct the prediction model, inclpuding Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Elastic Network Regression (Enet), Support Vector Machine (SVM), Logistic Regression, Multilayer Perceptron (MLP), and K-Nearest Neighbor (KNN). The prediction ability of each machine learning classifier was evaluated on the test set according to the evaluation index, and the &amp;quot;optimal&amp;quot; model of this study was selected. Subsequently, SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) were used to analyze the interpretability of the optimal model. &amp;lt;i&amp;gt;Results&amp;lt;/i&amp;gt;: The XGBoost model predicted the best performance among the 9 models. Its AUC value reached 0.908 and the clinical net benefit is the highest. The Delong test showed that there was a significant difference between the ROC curves of XGBoost and the other models (&amp;lt;I&amp;gt;P&amp;lt;/I&amp;gt;&amp;lt;0.05). The global interpretation based on SHAP showed that life satisfaction, self-rated health status, sleep duration, and cognitive score were inversely proportional to the SHAP value. Female, rural residents, body aches and pains in any area, non-retirement, and limited Instrumental Activities of Daily Living (IADL) have a positive effect on depression. The local interpretation diagram based on SHAP and LIME showed the personalized risk prediction of a single sample. &amp;lt;i&amp;gt;Conclusions:&amp;lt;/i&amp;gt; Machine learning models are an effectively tool for predict the risk of depression. The use of SHapley Additive exPlanations and Local Interpretable Model-agnostic Explanations can maximize the clinical advantages of machine learning, which is helpful to predict or detect patients at high risk of depression as early as possible, and to take comprehensive evaluation and early prevention and treatment of depression.

Организационно-методическая компетенция тренера в условиях производственной педагогической практики в сельской местности

In practice, physical education is an efficient measure for preventing antisocial behaviour among the population. This is especially relevant in rural areas. To date, rural areas of the country are characterised by a low development level of social and engineering infrastructure, compared to urban areas. In addition, there is a problem concerning the lack of funding for the development of sports infrastructure, the system of physical culture and sports events, as well as the attraction of sports personnel to rural settlements. These factors lead to a low level of physical training of children and young people in rural areas. In order to attract sports personnel to rural areas, the President of the Russian Federation Vladimir Putin has instructed to launch the federal programme ‘Zemsky trener [country trainer]’ from 2025, according to which every trainer who moves to a village, working-class settlement, urban-type settlement or town with a population of less than 50,000 people will receive a one-time payment of 1 million roubles. At present, physical training is of particular importance for rural residents as future specialists in the agro-industrial complex, since the country’s food security depends on the efficiency of the agricultural sector. Therefore, it is important to acquaint the rural youth with physical culture since their school days instilling a need for physical activity, which will ensure an optimal level of health, good physical fitness and high-performance capability of rural residents. All this cannot be achieved without a well-qualified trainer with the necessary competences.

Factors influencing high-risk fertility practices among women of childbearing age in Tanzania: using DHS 2022

BackgroundWomen’s high-risk fertility behavior, marked by short birth intervals, higher birth order, and early maternal age at childbirth, has been scientifically proven to have detrimental health effects on both the mother and child. Despite the recognized consequences, there is a limited body of research examining the factors that contribute to high-risk fertility behavior in Tanzania. Hence, this study seeks to identify the prevalence of high-risk fertility behavior and associated factors among women of reproductive age within the Tanzanian context.MethodThis study analyzed data from the 2022 Tanzania’s Demography and Health Survey, focusing on 11,380 women of childbearing age. To deal with the survey’s clustered structure and the binary nature of the outcome variable, a multi-level mixed-effect generalized linear model (Poisson regression with robust error variance) was employed. The Statistical significance of the predictor was assessed using adjusted prevalence ratios (aPR) with 95% confidence intervals.ResultsThe prevalence of high-risk fertility behavior among Tanzanian women was 71.55% (95% CI = 70.71, 72.37). Women’s educational levels, Age of women, wealth index, media exposure, decision-making autonomy, contraceptive use, and rural residence were found to be predictors of high-risk fertility behavior.Conclusiona considerable number of women in Tanzanian have encountered High-risk fertility Behaviors. This is a significant concern, posing a notable challenge to the healthcare system. Addressing this issue requires a comprehensive and coordinated approach that involves all stakeholders. Policymakers should consider developing programs that take into account predictors like wealth, education, and residence, which contribute to women’s vulnerability to high-risk fertility behavior. Focusing on women residing in areas with a high prevalence of high-risk fertility behavior could be instrumental in tackling the root causes of the problem.