Model Of Factors Research Articles

Facilitators, barriers, and strategies for supporting shared decision-making with people with intellectual disability: A West Australian primary healthcare professional perspective

ABSTRACT Background Shared decision-making between patients and primary healthcare professionals positively impacts health outcomes. However, people with intellectual disability face additional barriers and require supported shared decision-making (SSDM) to participate. Little is known about how healthcare professionals use SSDM with this population. This paper explores the facilitators and barriers experienced, and strategies/resources employed by healthcare professionals working with people with intellectual disability. Method Ten purposively sampled primary healthcare professionals participated in semi-structured interviews. This descriptive qualitative study used content analysis. Findings were compared with a proposed model of factors influencing triadic (the person with intellectual disability, their caregiver and the healthcare professional) SSDM. Results Five factor categories emerged: previous training/experience; engagement and trust; effective collaboration with caregivers; organisational culture and contexts; and familiarity/confidence with communication support strategies and resources. Conclusions Healthcare professionals can leverage pre-existing skills and knowledge, but provision of targeted professional development may reduce anxiety and increase successful SSDM.

Structural equation modeling: exploring relationships of body mass index, waist circumference, and hypertension in elderly

Waist circumference (WC) measurements in the elderly are uncommon and erratic. Furthermore, its correlation to hypertension has received less attention in Indonesia. This study attempted to investigate direct and indirect risk factors for high blood pressure in the elderly using structural equation modeling (SEM). A cross-sectional study was conducted in Surakarta, Central Java, Indonesia. The 297 elderly aged ≥60 is eager to take part. The path model of factors associated with blood pressure was analyzed using Stata 13. Male (b=-0.43; 95% CI=-5.67 to 4.81; p=0.872), age (b=0.52; 95% CI=0.12 to 0.93; p=0.012), and WC (b=0.35; 95% CI=0.17 to 0.53; p<0.001) directly affected systolic blood pressure (SBP). Male (b=1.83; 95% CI=-1.17 to 4.82; p=0.231), age (b=-0.03; 95% CI=-0.26 to 0.20; p=0.790), BMI (b=0.40; 95% CI=-0.03 to 0.83; p=0.067), and WC (b=0.04; 95% CI=-0.09 to 0.16; p=0.571) directly affected diastolic blood pressure (DBP). Increasing age, body mass index (BMI), and waist circumference (WC) are the important variables that influence blood pressure in older people. This study supports the evidence that body composition and weight control are necessary to prevent and control blood pressure in the elderly.

The Causal Model of Factors Affecting “Scientific Inquiry Ability”: A Survey of Lower Secondary School Students Using the Test of Integrated Process Skills, Focusing on their Indices for Proactive Attitude and Critical Thinking

The Causal Model of Factors Affecting “Scientific Inquiry Ability”: A Survey of Lower Secondary School Students Using the Test of Integrated Process Skills, Focusing on their Indices for Proactive Attitude and Critical Thinking

Effect of Regional Housing Hardship on Spatial Variation in Cancer Incidence: Does Housing Stress Increase Cancer Incidence?

Housing hardship can create a range of health issues. However, little attention has been paid to the relationship between housing hardship and cancer incidence. This study examines the Yangtze River Economic Belt (YREB) in China as a case study to develop a model of factors related to housing hardship that can affect cancer incidence. This study employs spatial regression models to investigate the correlation between housing hardship and cancer incidence and further explores the variation in the correlation between urban areas (UAs) and non-urban areas (NUAs). The research conclusions are as follows: (a) a palpable correlation exists between housing hardship and cancer incidence. The housing price-to-income ratio (HPIR) and the rental household proportion (RHP) are positively correlated to cancer incidence, whereas the per capita living area (PCLA) has a negative correlation with cancer incidence. (b) The differences in the impact of housing hardship on cancer incidence between the UAs and the NUAs are reflected mainly in the differences in the PCLA and the RHP. The PCLA has a strong association with cancer incidence in the UAs, whereas the RHP demonstrates a strong correlation with cancer incidence in the NUAs. (c) Significant spatial heterogeneity is observed in housing hardship in the YREB.

A structural model of factors influencing the introduction of neurobranding technologies

Subject. The article discusses neurobranding as a new research approach. Objectives. The focus is on the conceptualization of the structural model of factors influencing the introduction of neurobranding technologies. Methods. We developed a structural model of factors influencing the introduction of neurobranding technologies based on the metatheoretical method of cognition. Results. The paper established that the structural model of factors influencing the introduction of neurobranding technologies rests on four types of factors (technological, organizational, individual, and environmental) and expands the theoretical basis of research in the field of neurobranding. Conclusions. Technological, organizational, individual, and environmental factors can be used to study the implementation of neurobranding in various contexts. The identified factors have a positive or negative impact on the introduction of neurobranding technologies.

Towards a System Dynamics Model on Risk Factors of Knee Osteoarthritis: A Study Protocol for the DYNAMIKOS Model

(1) Background: Osteoarthritis (OA) is a serious chronic disease mostly affecting the knee joint. Despite the many efforts for developing strategies to predict and control Knee Osteoarthritis (KOA), the disease is on the rise. This paper describes the process for the creation of a simulation model, the Dynamic Knee Osteoarthritis Simulation (DYNAMIKOS) model, that captures the complex interrelationships of the risk factors for the development of KOA; (2) Methods: The DYNAMIKOS model will be based on the System Dynamics approach. The first step will be to develop a Causal Loop Diagram (CLD) model for the risk factors involved incorporating a series of Group Modeling Building (GMB) workshops with experts and stakeholders. Using data from a representative sample of KOA patients, the statistical approaches Exploratory Factor Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling (SEM) will be carried out. (3) Results: This study will develop a simulation System Dynamics model for the risk factors of KOA based on the results of CLD and SEM; (4) Conclusions: The proposed DYNAMIKOS model could be used for effectively analyzing the complex interrelationships among the multiple factors that constitute the spread of KOA. In this way, plausible prevention strategies could be implemented for effectively managing and leading the potential eradication of KOA.

A predictive and prognostic model for metastasis risk and prognostic factors in gastrointestinal signet ring cell carcinoma

BackgroundThis study aimed to predict metastasis risk and identify prognostic factors of gastrointestinal signet ring cell carcinoma (SRCC) using data from the SEER database, the largest cancer dataset in North America.MethodsData were obtained from the SEER database, covering 17 cancer registries from 2004 to 2020. Demographic and clinical data included sex, age, race, tumor location, size, pathological grade, stage, overall survival time, and treatment modalities. Statistical analyses were conducted using SPSS and R software. Propensity Score Matching (PSM) ensured comparable baseline characteristics between gastric cancer (GC) and colorectal cancer (CRC) groups. LASSO regression analysis identified predictors of metastasis, leading to the construction of predictive models using the lrm function in R. Nomograms were visualized with the “rms” package and assessed via ROC curves, calibration curves, and decision curve analysis (DCA). Cox regression analyses identified prognostic indicators for overall survival (OS), and Kaplan–Meier curves compared OS between high-risk and low-risk groups.ResultsFrom 2004 to 2020, 7680 SRCC patients were identified, including 4980 GC and 2700 CRC patients. CRC patients were older and had larger tumors, higher staging, and worse differentiation. Nomograms demonstrated good discriminative ability, with AUCs of 0.704 and 0.694 for GC, and 0.694 and 0.701 for CRC in training and validation cohorts, respectively. The DCA curve indicates that this predictive model has a high gain in predicting metastasis and OS.ConclusionsThe nomograms effectively predicted metastasis risk and OS in metastatic SRCC patients, offering clinical utility in stratifying patients and guiding treatment decisions, thereby enhancing personalized treatment approaches.

Developing A Conceptual Model of Factors Influencing Express Delivery Packaging Recycling Behaviors of E-Commerce Enterprises in China

The rapid growth of the e-commerce industry has led to a significant increase in express delivery service volumes, resulting in substantial environmental pollution and resource depletion from express delivery packaging (EDP) waste. Recycling express delivery packaging (EDPR) has become a critical global concern, particularly in China, the largest contributor to EDP waste for decades. Despite numerous government regulations aimed at promoting recycling behavior to support carbon peaking and neutrality targets, China’s recycling rate remains low, at just 25%-30%, compared to rates as high as 65% in EU countries, with some exceeding 80%. Drawing on Structuration Theory (ST), this study posits that the authority effect positively influences the recycling behavior of e-commerce organizations. It also examines the mediating role of recycling intention in the relationship between authority effect and recycling behavior and the moderating role of social sanction on recycling intention and behavior. This research aims to develop a comprehensive model for understanding the factors influencing EDPR and offers valuable insights from an organizational perspective. The findings will guide future empirical studies and help policymakers devise more effective strategies by understanding the impacts of authority and social sanction on recycling behavior.

Host Galaxy Demographics Of Individually Detectable Supermassive Black-hole Binaries with Pulsar Timing Arrays

Abstract Massive black hole binaries (MBHBs) produce gravitational waves (GWs) that are detectable with pulsar timing arrays. We determine the properties of the host galaxies of simulated MBHBs at the time they are producing detectable GW signals. The population of MBHB systems we evaluate is from the \textit{Illustris} cosmological simulations taken in tandem with post processing semi-analytic models of environmental factors in the evolution of binaries. Upon evolving to the GW frequency regime accessible by pulsar timing arrays, we calculate the detection probability of each system using a variety of different values for pulsar noise characteristics in a plausible near-future International Pulsar Timing Array dataset. We find that detectable systems have host galaxies that are clearly distinct from the overall binary population and from most galaxies in general. With conservative noise factors, we find that host stellar metallicity, for example, peaks at $\sim2Z_\odot$ as opposed to the total population of galaxies which peaks at $\sim0.6Z_\odot$. Additionally, the most detectable systems are much brighter in magnitude and more red in color than the overall population, indicating their likely identity as large ellipticals with diminished star formation. These results can be used to develop effective search strategies for identifying host galaxies and electromagnetic counterparts following GW detection by pulsar timing arrays.

Parental Burnout-A Model of Risk Factors and Protective Resources Among Mothers of Children with/Without Special Needs.

Parents of children With Special Needs and Disabilities (W-SND) who require long-term healthcare are at high risk of Parental Burnout (PB). However, most studies have focused on PB among parents of children Without Special Needs (WO-SN). This study aimed to develop a new model explaining PB of mothers of children W-SND/WO-SN. The main hypothesis was that the nexus of correlations between risk factors of PB (severity of child's disability/challenge, perceived caregiver burden) and protective resources (social support, learned resourcefulness, deep emotion work) will explain the variance of PB of mothers of children W-SND and WO-SN. A questionnaire assessing PB, its risk factors, and protective resources was completed by 352 Israeli mothers of children W-SND (mean age 36.9) or WO-SN (mean age 32.3). The child's disabilities were communicative, physical, intellectual and developmental. The main results are that mothers of children W-SND reported higher PB, higher caregiver burden, and a higher severity of disability. About 50% of PB variance was significantly explained by the nexus of correlations between selected risk and protective factors. Among all mothers, the more social support they received, the higher their learned-resourcefulness. However, learned resourcefulness mediates the correlation between caregiver burden and PB among mothers of children W-SND. Accordingly, it is important to increase awareness among healthcare professionals regarding the risk factors and symptoms of PB, and to develop workshops on protective resources in order to prevent PB and promote mothers' well-being. Further research should be conducted among fathers and parents from diverse cultures.

Corporate Technology for the Implementation of an Automated System: Functional, Technological and Methodological Aspects

The purpose of the study is to form a methodological justification for the pedagogical model of the individual trajectory of professional development of bachelors and masters for the implementation of the stages of creating an automated system based on the principles of continuity and experimental verification of its application in the educational process of the university in accordance with the requirements of IT departments, vendors and employers. It is shown that there is a gap between the socio-economic order for the training of IT specialists with high professional competence in the field of information systems and the insufficient level of targeted formation of their readiness to implement the stages of creating automated systems. In addition, the lack of methods and practical recommendations for the implementation of such systems in the context of maximum preservation of corporate standards and taking into account the requirements of Russian legislation, as well as specialists competent in these matters, determined the feasibility of conducting the study in two aspects - functional-technological and pedagogical.Methods and materials. The key methods are structural-functional and process modeling, interactive methods of organizing the educational process (project method, etc.). The research materials include a functional model for developing a corporate technology for implementing an automated system in the form of a function tree.Results. The results present a model of causes and factors determining the success of the projects for the implementation of the automatization systems. The role of the factor “qualification of the performing team” and the possibilities of the educational environment of the university to influence this factor are considered. The pedagogical aspect of the research problem is determined by the methodological justification for conducting students’ project work within a number of disciplines for training bachelors and masters in the field of “Applied Informatics”. The description of the structure and requirements for students’ projects gives an idea of the level of formed competencies, their consistency with the work functions of specialists in the field of information systems.Conclusion. At this stage of work on the research problem, its dual nature was determined. On the one hand, modern IT projects require their own technologies and management methodologies, which should change from project to project, so it is important to have practical recommendations for the development of corporate technology for the implementation of an automated system. On the other hand, one of the success factors of the project for the implementation of an automated system is the “Project Implementation Team”, its level of qualification. This factor is successfully determined and influenced by educational institutions responsible for training specialists in this field. In this direction, the project method plays a key role. It ensures the development of communication skills, the ability to independently pose a problem and develop a way to solve it together. Methodological aspects and practical results, generalizing the pedagogical model for training bachelors in the field of creating automated systems presented in the paper, as well as the development of corporate technology for the implementation of information systems, were reflected in three electronic multimedia educational publications: “Portfolio of Software Engineering Projects”, “Theory and Practice of IS Implementation”, “Theory and Practice of IS Maintenance”.

Incidence, risk factors for metabolic syndrome and health systems capacity for its management amongst people living with HIV, Accra-Ghana: A study protocol.

Metabolic syndrome (MetS) refers to the clustering of three or more metabolic disorders including high blood pressure, glucose impairment, abdominal obesity, high triglycerides, and low high-density lipoproteins. MetS is increasingly being considered an epidemic among People Living With HIV (PLWH) with reports of association between HIV infection and/or antiretroviral therapy (ART) usage and development of MetS. MetS predisposes PLWH to the development of cardiovascular, kidney diseases and diabetes, decreases the quality of life, and burdens the health system. This study aims to establish the incidence, time to development and risk factors for development of MetS and it's components, and to assess the capacity of the health system to manage MetS and it's components among ART naive PLWH in Accra, Ghana. We will conduct a mixed methods study with quantitative and qualitative data collection. Our prospective cohort study would enroll adults of 18 years and above with none or less than three MetS components at baseline and follow them up at six months and one year. Demographic, lifestyle data, anthropometric, and laboratory data will be collected using an adapted WHO Steps Survey questionnaire. The WHO Service Availability and Readiness Questionnaire (SARA) will be adapted to collect information on capacity across the six WHO building blocks. Key informant interviews will be conducted with HIV coordinators at the national, regional, and facility levels. In-depth interviews will be conducted with PLWH from the cohort who develop MetS or MetS components during their follow-up. Data will be analysed using proportions, Kaplan Mier time to event analysis, fitting of Cox proportional hazard regression models for risk factors, and generation of themes from qualitative data. This study will generate data on the incidence, time to development, risk factors for MetS and MetS components development, and health systems capacity for MetS management among PLWH. Findings would inform revisions to the guidelines and policies for HIV care in Ghana, Africa, and beyond, ultimately improving MetS prevention and management among the vulnerable population of PLWH.

The Relationship Between Avatar Identification Factors and Vicarious Pleasure: The Moderating Role of Affect Intensity in the Metaverse

This study investigated the connection between avatar identification factors, sharing intentions, and the influence of vicarious pleasure. Additionally, it explored the moderating effect of affect intensity on this relationship. For this, data was collected from 228 college students in South Korea through a survey. This study used hierarchical regression. The findings revealed several key points. Firstly, participants who perceived greater similarity identification, wishful identification, and embodied presence in their avatars within the metaverse platform reported higher satisfaction with their avatars. Secondly, participants who experienced a higher sense of embodied presence in their avatars were more inclined to share their avatars due to the vicarious pleasure they derived from it. Lastly, the positive correlation between perceived embodied presence and vicarious pleasure was stronger for participants with higher affect intensity in the metaverse platform. This study is the first to examine the integral model of avatar identification factors in the metaverse platform.

Bayesian clustering of high-dimensional data via latent repulsive mixtures

SUMMARY Model-based clustering of moderate or large dimensional data is notoriously difficult. We propose a model for simultaneous dimensionality reduction and clustering by assuming a mixture model for a set of latent scores, which are then linked to the observations via a Gaussian latent factor model. This approach was recently investigated by Chandra et al. (2023). The authors use a factor-analytic representation and assume a mixture model for the latent factors. However, performance can deteriorate in the presence of model misspecification. Assuming a repulsive point process prior for the component-specific means of the mixture for the latent scores is shown to yield a more robust model that outperforms the standard mixture model for the latent factors in several simulated scenarios. The repulsive point process must be anisotropic to favour well-separated clusters of data, and its density should be tractable for efficient posterior inference. We address these issues by proposing a general construction for anisotropic determinantal point processes. We illustrate our model in simulations as well as a plant species co-occurrence dataset.

The Effects of money supply on Economic Growth of Laos

This research aims to analyze the effect of money supply volume on the economic growth of Lao PDR. Using secondary data annually from 2012–2022. which uses the multiple regression equation (multiple regression) with the method of least squares (OLS) to estimate the coefficients of dependent variables and independent variables, starting from checking the properties of the unit root data using the Augmented Dick Fuller test statistic method to test the data. Through checking the properties of the model of external factors that affect the amount of money supply (M2), it was found that the coefficient of decision Adjusted R Square = 0.9931, which means that the independent variables Gross National Income (GNI), Exchange Rate (Exr), and Consumer Price Index (CPI) can explain the variable according to the amount of money (M2) determined up to 99.31%; the rest depends on other factors that are not included in the study. Therefore, the model of external factors that affect the amount of money M2 can be used and depends on at least one factor identified. Also, by bringing the data to test the effect of the independent variable on the dependent variable in the long term and in the short term, ECM(-1) found that the model that simulates the effect of the amount of money M2 on the economic growth of the Lao PDR in the long-term equilibrium state (co-integration) and in the short-term equilibrium state (Error Correction Model: ECM) is not applicable and does not depend on the identified factors. But it will have a long-term effect, which, through checking the properties of the model from a long-term perspective, found that the coefficient of decision Adjusted R Square = 0.6877, which means that the independent variable M2 money can explain the variable according to the economic growth rate determined in the long term up to 68.77%. The change in the money M2 in the short term does not affect the economic growth rate of the Lao PDR, but the change in the money M2 in the long term will definitely affect the economic growth rate.

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Unplanned Reoperation Postspinal Surgery Within 30 Days

Unplanned reoperation post-spinal surgery (URPS) leads to prolonged hospital stays, higher costs, decreased patient satisfaction, and adversely affects postoperative rehabilitation. This study aimed to develop and validate prediction models (nomograms) for early URPS risk factors using machine learning (ML) methods, aiding spine surgeons in designing prevention strategies, promoting early recovery, reducing complications and improving patient satisfaction. Medical records of 639 patients who underwent reoperation post-spinal surgery (RPS) from the First Affiliated Hospital of Air Force Medical University (2018 - 2022) were collected, including baseline indicators, perioperative indicators, and laboratory indicators. After applying inclusion and exclusion criteria, 122 URPS and 155 non-URPS patients were identified and randomly divided into training (82 URPS, 111 non-URPS) and validation (40 URPS, 44 non-URPS) cohorts. Three ML methods (LASSO regression, Random Forest, and SVM-RFE) were used to select feature variables, and their intersection was used to develop the prediction model, tested on the validation cohort. Six factors-implant, postoperative suction drainage (PSD), gelatin sponge (GS), anticoagulants (ATG), antibiotics (ATB), and disease type (DT)-were identified to construct a nomogram diagnostic model. The area under the curve (AUC) of this nomogram was 0.829 (95% CI 0.771-0.886) in the training cohort and 0.854 (95% CI 0.775-0.933) in the validation cohort. Calibration curves demonstrated satisfactory agreement between predictions and actual probabilities. The decision curve indicated clinical usefulness with a threshold between 1% and 90%. The established model can effectively predict URPS in patients and can assist spine surgeons in devising personalized and rational clinical prevention strategies.

An investigation of multimodal predictors of adolescent alcohol initiation

BackgroundEarly alcohol initiation is associated with negative, alcohol-related outcomes. While previous work identifies numerous risk factors for early use, the relative contributions of known predictors remains understudied. The current project addresses this gap by 1) prospectively predicting early alcohol initiation using measures of inhibition control, reward sensitivity, and contextual risk factors and 2) interrogating the relative importance of each domain. MethodThis study leverages multimodal data from substance-naïve youth enrolled in the Adolescent Brain Cognitive Development (ABCD) Study® (n=11,694). Early initiation was defined as consuming a full standard drink containing alcohol prior to age 16. Propensity scores were used to match alcohol initiators (n=348) with demographically similar non-initiators at a 1:2 ratio (n=696). Independent logistic regressions were conducted for each domain followed by additive, hierarchical models. ResultsThe model of contextual factors (pseudo-R2=0.086, AUC=0.67) outperformed inhibition control (pseudo-R2=0.021, AUC=0.58) and reward sensitivity measures (pseudo-R2=0.020, AUC=0.59). The hierarchical model containing all measures (pseudo-R2=0.106, AUC=0.69) did not significantly improve the model of contextual factors alone (p>0.05). Examples of significant predictors (p<0.05) include externalizing behaviors, number of substances known, and non-religious alcohol sipping. ConclusionContextual risk factors were the strongest predictors of early alcohol use; however, more work is needed to understand the causal nature of this relationship. Measures of inhibition control and reward sensitivity were not adequate in distinguishing initiators from non-initiators. These findings add to a body of evidence that contextual factors play a major role in alcohol initiation while highlighting specific predictor variables that could inform youth alcohol prevention.

A qualitative investigation of crisis cafés in England: their role, implementation, and accessibility

BackgroundCrisis cafés (also known as crisis sanctuaries or havens) are community-based services which support people in mental health crises, aiming to provide an informal, non-clinical and accessible setting. This model is increasingly popular in the UK; however, we are aware of no peer-reviewed literature focused on this model. We aimed to investigate the aims of crisis cafés, how they operate in practice and the factors that affect access to these services and implementation of the intended model.MethodsA qualitative approach was used. Semi-structured interviews were conducted with 12 managers of crisis cafés across England. These interviews explored managers’ views on the implementation of their services, and the factors that help and hinder successful implementation. Data were analysed using Braun and Clarke’s reflexive thematic approach.ResultsWe identified five main perceived aims for crisis cafés: providing an alternative to Emergency Departments; improving access to crisis care; providing people in acute distress with someone to talk to in a safe and comfortable space; triaging effectively; and improving crisis planning and people’s coping skills. Factors seen as influencing the effectiveness of crisis cafés included accessibility, being able to deliver person-centred care, relationships with other services, and staffing. These factors could both help and hinder access to care and the implementation of the intended model. There were a number of trade-offs that services had to consider when designing and running a crisis café: (1) Balancing an open-door policy with managing demand for the service through referral routes, (2) Balancing risk management procedures with the remit of offering a non-clinical environment and (3) Increasing awareness of the service in the community whilst avoiding stigmatising perceptions of it.ConclusionsFindings illustrate the aims of the crisis café model of care and factors which are influential in its implementation in current practice. Future research is needed to evaluate the efficacy of these services in relation to their aims. Crisis café service users’ views, and views of stakeholders from the wider crisis care system should also be ascertained.

Research on Factors Influencing Housing Price based on Principle Component Analysis and Polynomial Regression

Housing price is influenced by natural, social, economic and other factors. Only by understanding and conducting specific research on these influencing factors can people grasp the laws of housing price movements. Focusing on this issue, this paper chooses the average unit housing prices and their influencing factors of 11 cities in Zhejiang Province in 2022 as the research objects, then establishes a model reflecting the quantitative relationship between housing price and influencing factors. Firstly, relevant data is collected from official websites, including housing prices and 10 main influencing factor indicators of above cities. Secondly, principal component analysis is used for data preprocessing, and five prominent indicators are selected by calculating the relative contribution rate of each factor. Then, by drawing functional images and solving correlation coefficients, a qualitative analysis is conducted on the basic algebraic structure of the regression model. The results indicate that all independent variables include independent terms and cross-terms. Subsequently, through polynomial regression, data matrices for both dependent variable and independent variables are set to solve the coefficients of constant term, linear terms, quadratic independent terms and quadratic cross-terms respectively. Therefore, a model of factors influencing housing price is established. Finally, residuals sum of squares, mean square error, regression sum of squares and determination coefficient are calculated in sequence for the regression model. It turns out that all the statistics are within the ideal range, indicating high precision of data fitting and verifying the accuracy and reliability of the model.

Interrogating the environmental and social correlates of health risk behaviours in West Africa

Abstract Background Despite the high incidences of health risk behaviors (HRBs) in sub-Saharan Africa, studies on the contextual determinants of HRBs across countries are generally lacking, concentrated on isolated countries and often focus solely on specific health behaviors. Thus, this study investigated the environmental and social correlates of HRBs in West Africa. Methods Data was from post-2015 Demographic and Health Surveys in three West African countries of Benin, Mali and Nigeria. A composite outcome variable of health risk behaviors (HRBs) was derived from variables of tobacco smoking, intimate partner violence, overweight/obesity and risky sexual behaviors. The contextual variables were normalized difference vegetation index, precipitation, maximum and minimum temperatures, region of residence and population Density. Data analysis involved descriptive statistics, chi square test, geographical mapping, and multilevel logistic regression. Results The engagement in HRBs varied from 42.65% in Nigeria to 42.88% in Benin and 51.06% in Mali as there are spatial variations in the engagement in HRBs within different regions of these countries. There also existed significant variations in HRBs regarding age, education, employment status, wealth index, household size, place of residence, and region of residence in the three countries. In the contextual models of environmental and social factors, population density significantly increased odds of HRBs in the three countries, maximum temperature significantly increased odds of HRBs in Benin and Mali, while precipitation significantly increased odds of HRBs in Nigeria and Mali. Other factors which significantly increased odds of HRBs across the three countries were increase in age, wealth index, households with 9+ persons, and regions of residence. Conclusions These findings suggest that among other things, changes in lifestyles regarding the different HRBs should be emphasized in specific contextual situations Key messages • There are variations in engagement in health risk behaviours across the countries. • Cliamte variables influence engagement in health risk behaviours.