Factor associated with tobacco use among the adult population in Sarawak, Malaysia: a cross sectional study

Introduction: Consumption of tobacco in any form is one of the leading causes of preventable mortality. The World Health Organization recommends that it should be monitored regularly.  This study was designed to estimate the prevalence of tobacco use among the rural adult population in Sarawak and factors associated with it. Methods: This was a cross-sectional study conducted among the adult population in Sarawak. Data were collected from ten villages in Kota Samarahan and Kuching Division by face to face interview using modified Global Adult Tobacco Survey questionnaire. Non-probability sampling method was adopted to select the villages. All the households of the villages were visited and an adult member was selected randomly from each house irrespective of the sex. After missing value imputation, 1000 data were analysed using statistical software SPSS 19.0 version. Results: Analysis showed that 30.9% of the respondents were current tobacco users and 11% were past tobacco users. The mean age (SD) at starting tobacco was 18.1 (6.48) years. The frequency of tobacco use was 14 times per day.  Hierarchical Logistic regression analysis revealed that age with male sex (OR=1. 064, 95% CI: 1.052, 1.076), secondary education (OR=-2.712; 95% CI: 1.122, 6.555), higher secondary and above (OR=3. 571; 95% CI: 1.641,7.774), occupation as business (OR=3. 152; 95% CI: 1.732, 5.735) and environmental exposure such as smoking at working place (OR=2. 754;95% CI: 1.895,4.002), coffee house (OR=2. 274;95% CI: 1.32,3.919) and at home (OR=1. 827;95% CI: 1.242,2.687) appeared to be  important predictors of tobacco use (p<0.05). Conclusion: A large proportion of males use tobacco products. Though tobacco use was negligible among females, but they would be potential users. Environmental exposure to tobacco appeared to be important predictors. Tobacco control campaigns should target banning of tobacco use in closed and open areas and also to intensify the monitoring of all forms of tobacco used by the population

Mapping and Deep Analysis of Image Dehazing: Coherent Taxonomy, Datasets, Open Challenges, Motivations, and Recommendations

Our study aims to review and analyze the most relevant studies in the image dehazing field. Many aspects have been deemed necessary to provide a broad understanding of various studies that have been examined through surveying the existing literature. These aspects are as follows: datasets that have been used in the literature, challenges that other researchers have faced, motivations, and recommendations for diminishing the obstacles in the reported literature. A systematic protocol is employed to search all relevant articles on image dehazing, with variations in keywords, in addition to searching for evaluation and benchmark studies. The search process is established on three online databases, namely, IEEE Xplore, Web of Science (WOS), and ScienceDirect (SD), from 2008 to 2021. These indices are selected because they are sufficient in terms of coverage. Along with definition of the inclusion and exclusion criteria, we include 152 articles to the final set. A total of 55 out of 152 articles focused on various studies that conducted image dehazing, and 13 out 152 studies covered most of the review papers based on scenarios and general overviews. Finally, most of the included articles centered on the development of image dehazing algorithms based on real-time scenario (84/152) articles. Image dehazing removes unwanted visual effects and is often considered an image enhancement technique, which requires a fully automated algorithm to work under real-time outdoor applications, a reliable evaluation method, and datasets based on different weather conditions. Many relevant studies have been conducted to meet these critical requirements. We conducted objective image quality assessment experimental comparison of various image dehazing algorithms. In conclusions unlike other review papers, our study distinctly reflects different observations on image dehazing areas. We believe that the result of this study can serve as a useful guideline for practitioners who are looking for a comprehensive view on image dehazing

Adaptive Deep Learning Detection Model for Multi-Foggy Images

The fog has different features and effects within every single environment. Detection whether there is fog in the image is considered a challenge and giving the type of fog has a substantial enlightening effect on image defogging. Foggy scenes have different types such as scenes based on fog density level and scenes based on fog type. Machine learning techniques have a significant contribution to the detection of foggy scenes. However, most of the existing detection models are based on traditional machine learning models, and only a few studies have adopted deep learning models. Furthermore, most of the existing machines learning detection models are based on fog density-level scenes. However, to the best of our knowledge, there is no such detection model based on multi-fog type scenes have presented yet. Therefore, the main goal of our study is to propose an adaptive deep learning model for the detection of multi-fog types of images. Moreover, due to the lack of a publicly available dataset for inhomogeneous, homogenous, dark, and sky foggy scenes, a dataset for multi-fog scenes is presented in this study (https://github.com/Karrar-H-Abdulkareem/Multi-Fog-Dataset). Experiments were conducted in three stages. First, the data collection phase is based on eight resources to obtain the multi-fog scene dataset. Second, a classification experiment is conducted based on the ResNet-50 deep learning model to obtain detection results. Third, evaluation phase where the performance of the ResNet-50 detection model has been compared against three different models. Experimental results show that the proposed model has presented a stable classification performance for different foggy images with a 96% score for each of Classification Accuracy Rate (CAR), Recall, Precision, F1-Score which has specific theoretical and practical significance. Our proposed model is suitable as a pre-processing step and might be considered in different real-time applications

Factor associated with tobacco use among the adult population in Sarawak, Malaysia: a cross sectional study

Introduction: Consumption of tobacco in any form is one of the leading causes of preventable mortality. The World Health Organization recommends that it should be monitored regularly. This study was designed to estimate the prevalence of tobacco use among the rural adult population in Sarawak and factors associated with it. Methods: This was a cross-sectional study conducted among the adult population in Sarawak. Data were collected from ten villages in Kota Samarahan and Kuching Division by face to face interview using modified Global Adult Tobacco Survey questionnaire. Non-probability sampling method was adopted to select the villages. All the households of the villages were visited and an adult member was selected randomly from each house irrespective of the sex. After missing value imputation, 1000 data were analysed using statistical software SPSS 19.0 version. Results: Analysis showed that 30.9% of the respondents were current tobacco users and 11% were past tobacco users. The mean age (SD) at starting tobacco was 18.1 (6.48) years. The frequency of tobacco use was 14 times per day. Hierarchical Logistic regression analysis revealed that age with male sex (OR=1. 064, 95% CI: 1.052, 1.076), secondary education (OR=-2.712; 95% CI: 1.122, 6.555), higher secondary and above (OR=3. 571; 95% CI: 1.641,7.774), occupation as business (OR=3. 152; 95% CI: 1.732, 5.735) and environmental exposure such as smoking at working place (OR=2. 754;95% CI: 1.895,4.002), coffee house (OR=2. 274;95% CI: 1.32,3.919) and at home (OR=1. 827;95% CI: 1.242,2.687) appeared to be important predictors of tobacco use (p<0.05). Conclusion: A large proportion of males use tobacco products. Though tobacco use was negligible among females, but they would be potential users. Environmental exposure to tobacco appeared to be important predictors. Tobacco control campaigns should target banning of tobacco use in closed and open areas and also to intensify the monitoring of all forms of tobacco used by the population

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Evaluating the level of primary school students in the light of reading skills

The aim of the current research is to (evaluating the level of primary school students in the light of reading skills), and to achieve this, the researcher relied on the descriptive approach, and a research tool was built, which is the questionnaire, which consisted of (22) paragraphs distributed on six main skills: recognition, pronunciation, understanding, taste, criticism. , the evaluation and put three alternatives for each paragraph (available, available to some extent, not available), and the researcher made sure of the validity and reliability of the tool. , Hashemite District, amounted to (382) male and female students for the academic year (2021-2022 AD) and after applying the tool and unloading the data, analyzing it and treating it statistically with the Statistical Package for Social Sciences (SPSS).The researcher reached a number of results, the most important of which are: The level of availability of reading skills for primary school students (fifth grade of primary school) was very poo

Factors associated with tobacco use among the adult population in sarawak, malaysia:a cross sectional study

Background: Consumption of tobacco in any form is one of the leading causes of preventable mortality. The World Health Organization recommends that it should be monitored regularly. A study was conducted to estimate the prevalence of tobacco use and factors associated with it among rural adult population in Sarawak. Methods: This was a cross-sectional study conducted among the adult population. Data were collected from ten Kampungs (villages) in Kota Samarahan and Kuching Division by face-to-face interview using modified Global Adult Tobacco Survey (GA TS) questionnaire. Non-probability sampling method was adopted to select the villages. All the households of the selected villages were visited and an adult member, irrespective of sex, was selected randomly from each household. The study was conducted for a period of one year from July 2012 to June 2013. After missing value imputation, 1000 data were analysed using statistical software SPSS 19.0 version. Results: Analysis showed that 30.9% of the respondents were current tobacco users and 11% were past tobacco users. The mean age (SD) of starting tobacco use was 18.1 (6.48) years. The mean frequency of tobacco use was 14 times per day. Hierarchical Logistic regression analysis revealed that age with male sex (OR=1.064, 95% CI: 1.052, 1.076), secondary education (OR=-2.712; 95% CI: 1.122, 6.555), higher secondary and above (OR=3. 571; 95% CI: 1.641,7.774), business as occupation (OR =3.152; 95% CI: 1.732, 5.735) environmental exposure such as smoking at working place (OR=2.754;95% CI: 1.895,4.002), coffee house (OR=2. 274;95% CI: 1.32,3.919) and at home (OR=1. 827;95% CI: 1.242,2.687) appeared to be important predictors of tobacco use (p<0.05). ConclusionS: A large proportion of males used tobacco products. Though tobacco use was negligible among females, nonetheless they would be potential users. Environmental exposure to tobacco appeared to be important predictors. Tobacco control campaigns should target banning of tobacco use in more closed and open areas and also to intensify the monitoring of all forms of tobacco used by the populatio

Adaptive deep learning detection model for multi-foggy images

The fog has different features and effects within every single environment. Detection whether there is fog in the image is considered a challenge and giving the type of fog has a substantial enlightening effect on image defogging. Foggy scenes have different types such as scenes based on fog density level and scenes based on fog type. Machine learning techniques have a significant contribution to the detection of foggy scenes. However, most of the existing detection models are based on traditional machine learning models, and only a few studies have adopted deep learning models. Furthermore, most of the existing machines learning detection models are based on fog density-level scenes. However, to the best of our knowledge, there is no such detection model based on multi-fog type scenes have presented yet. Therefore, the main goal of our study is to propose an adaptive deep learning model for the detection of multi-fog types of images. Moreover, due to the lack of a publicly available dataset for inhomogeneous, homogenous, dark, and sky foggy scenes, a dataset for multi-fog scenes is presented in this study (https://github.com/Karrar-H-Abdulkareem/Multi-Fog-Dataset). Experiments were conducted in three stages. First, the data collection phase is based on eight resources to obtain the multi-fog scene dataset. Second, a classification experiment is conducted based on the ResNet-50 deep learning model to obtain detection results. Third, evaluation phase where the performance of the ResNet-50 detection model has been compared against three different models. Experimental results show that the proposed model has presented a stable classification performance for different foggy images with a 96% score for each of Classification Accuracy Rate (CAR), Recall, Precision, F1-Score which has specific theoretical and practical significance. Our proposed model is suitable as a pre-processing step and might be considered in different real-time applications.Web of Science77372

Surgical site infection after gastrointestinal surgery in children : an international, multicentre, prospective cohort study

Introduction Surgical site infection (SSI) is one of the most common healthcare-associated infections (HAIs). However, there is a lack of data available about SSI in children worldwide, especially from low-income and middle-income countries. This study aimed to estimate the incidence of SSI in children and associations between SSI and morbidity across human development settings. Methods A multicentre, international, prospective, validated cohort study of children aged under 16 years undergoing clean-contaminated, contaminated or dirty gastrointestinal surgery. Any hospital in the world providing paediatric surgery was eligible to contribute data between January and July 2016. The primary outcome was the incidence of SSI by 30 days. Relationships between explanatory variables and SSI were examined using multilevel logistic regression. Countries were stratified into high development, middle development and low development groups using the United Nations Human Development Index (HDI). Results Of 1159 children across 181 hospitals in 51 countries, 523 (45 center dot 1%) children were from high HDI, 397 (34 center dot 2%) from middle HDI and 239 (20 center dot 6%) from low HDI countries. The 30-day SSI rate was 6.3% (33/523) in high HDI, 12 center dot 8% (51/397) in middle HDI and 24 center dot 7% (59/239) in low HDI countries. SSI was associated with higher incidence of 30-day mortality, intervention, organ-space infection and other HAIs, with the highest rates seen in low HDI countries. Median length of stay in patients who had an SSI was longer (7.0 days), compared with 3.0 days in patients who did not have an SSI. Use of laparoscopy was associated with significantly lower SSI rates, even after accounting for HDI. Conclusion The odds of SSI in children is nearly four times greater in low HDI compared with high HDI countries. Policies to reduce SSI should be prioritised as part of the wider global agenda.Peer reviewe