scholarly journals Support for smoke-free policy among Malaysian adults: findings from a population-based study

BMJ Open ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. e020304 ◽  
Author(s):  
Lim Kuang Hock ◽  
Lim Hui Li ◽  
Teh Chien Huey ◽  
Veloo Yuvaneswary ◽  
Pan Sayan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Public Opinion ◽  
Public Transport ◽  
Adult Population ◽  
Sampling Strategy ◽  
Smoking Behaviour ◽  
Smoking Ban ◽  
Multiple Logistic Regression ◽  
Shopping Centres ◽  
Smoke Free Policy

ObjectivePublic opinion and support can be powerful mandates for smoke-free policy. However, the scarcity of evidence on public opinion among Malaysians necessitates further investigation. Therefore, this study aimed to determine the level of support for smoke-free policy at various public domains and its associated factors among Malaysian adults.DesignData were derived from the Global Adult Tobacco Survey, Malaysia (GATS-M). GATS-M is a nationwide study that employed a multistage, proportionate-to-size sampling strategy to select a representative sample of 5112 Malaysian adults aged 15 years and above. Multiple logistic regression was used to identify factors associated with support for smoke-free policy in selected public domains that is, workplaces, restaurants, bars, hotels, casinos, karaoke centres, public transport terminals and shopping centres.ResultsThe level of support for enactment of a smoke-free policy at selected public domains varied from 37.8% to 94.4%, with the highest support was for gazetted smoke-free domains, namely, shopping centres (94.4%, 95% CI: 93.2% to 95.3%) and public transport terminals (85.2%, 95% CI: 83.3% to 86.9%). Multiple logistic regression revealed that non-smokers were more likely to support smoke-free policy at all domains. In addition, respondents who worked in workplaces with total or partial smoking restrictions were more likely to support a smoke-free policy ((total restriction adjusted OR (AOR): 14.94 (6.44 to 34.64); partial restriction AOR: 2.96 (1.138 to 6.35); non-restriction was applied as a reference).ConclusionA majority of the Malaysian adult population supported the smoke-free policy, especially at gazetted smoke-free domains. Therefore, expansion of a total smoking ban to workplaces, restaurants, bars, hotels, casinos and karaoke centres is strongly recommended to reduce exposure to secondhand smoke and to denormalise smoking behaviour.

scholarly journals THE MODE CHOICES AND COMMUTING STRESS: EMPIRICAL EVIDENCE FROM JAKARTA AND DENPASAR

2019 ◽  
Vol 7 (1) ◽  
pp. 68
Author(s):  
Ismatulloh Rosida ◽  
Dyah Wulan Sari ◽  
Amelia Dertta Irjayanti
Keyword(s):  
Logistic Regression ◽  
Public Transport ◽  
Regression Models ◽  
Toll Roads ◽  
Multiple Logistic Regression ◽  
Logistic Regression Models ◽  
High Impedance ◽  
Logistic Regressions ◽  
Using Data ◽  
The Relationship

Jabodetabek and Sarbagita have the highest worker commuter population in Indonesia. However, Jabodetabek has various and larger coverage of public transport than Sarbagita. This study also analyzes the relationship between the usage of specific transport modes and commuting stress. Multiple logistic regression models have been estimated using data of both Jabodetabek Commuter Survey and Sarbagita Commuter Survey. Using logistic regressions, the results show that mode choices, gender, and travel time have a significant effect on commuting stress. The analysis also indicates that both in high impedance and low impedance metropolitans, car commuting is perceived to be more stressful than non-car commuting. In a condition of restricted mode choices, commuters who use cars have a greater probability of commuting stress. Furthermore, the findings of this study imply limitation of car usage and as an evaluation of the policy of opening toll roads as a solution to urban congestion.

scholarly journals Knowledge, Attitude and Practice on Dengue among Adult Population in Felda Sungai Pancing Timur, Kuantan, Pahang

2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Karimah Hanim AA ◽  
Razman MR ◽  
Jamalludin AR ◽  
Nasreen EH ◽  
Htike Myat Phyu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Adult Population ◽  
Descriptive Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Behavioral Problem ◽  
Breeding Site ◽  
Multiple Logistic Regression ◽  
Cross Sectional ◽  
Attitude And Practice ◽  
Knowledge Attitude And Practice

Background: With increasing number of dengue cases in Malaysia, it’s of utmost importance that immediate action be taken to limit the epidemic. Since dengue control is a behavioral problem, the knowledge, attitude and practice in population needs to be studied in order to control the disease. Hence, the aim of this study is to assess knowledge, attitude and practice regarding dengue and its associated factors among adult residents of Felda Sungai Panching Timur (SPT), Kuantan, Pahang, 2014. Method: A cross sectional study was carried out involving 265 adult respondents. A face to face  interview questionnaire which was divided into 2 parts (Part A: Sociodemoghraphic; Part B: Knowledge, Attitude and Practice) was used. Data was analyzed using descriptive statistics, simple and multiple logistic regression. Results: 53.2% of the respondents had good knowledge about dengue and it was found that the main source of information from mass media (76.6%). However, only 43.4% were found to have good attitude towards dengue. Multiple Logistic Regression analysis showed there was no association between sociodemographic characteristics with the level of knowledge and attitude towards dengue. There was also no association found between knowledge of dengue and the attitude of the respondents towards dengue. Descriptive analysis on the practice of dengue showed majority of the respondents who had possible breeding site for Aedes mosquitos (water container, drains/gutter roof/flower pots/tires) in their compound practiced good habit in preventing the Aedes mosquitoes from breed. Conclusion: Although knowledge and practice towards dengue is good, their attitude require improvement.

scholarly journals Predictors of influenza in the adult population during seasonal and A(H1N1)pdm09 pandemic influenza periods

2013 ◽  
Vol 142 (5) ◽  
pp. 950-954 ◽  
Author(s):  
G. GEFENAITE ◽  
M. TACKEN ◽  
J. KOLTHOF ◽  
B. MULDER ◽  
J. C. KOREVAAR ◽  
...  
Keyword(s):  
Logistic Regression ◽  
General Population ◽  
Clinical Characteristics ◽  
Seasonal Influenza ◽  
Adult Population ◽  
Vaccination Status ◽  
Multiple Logistic Regression ◽  
Population Database ◽  
Different Seasons ◽  
Status Information

SUMMARYWe aimed to assess whether the characteristics of influenza-like illness (ILI) cases in the general population were similar during the seasonal and pandemic A(H1N1)pdm09 influenza periods. We conducted a study using a general population database, which included demographic (sex, age) and clinical (underlying medical conditions, influenza vaccination status) information on more than 80 000 subjects. We assessed the most important predictors of ILI during each season by using multiple logistic regression. We descriptively compared whether they were similar during different seasons. The model, including all demographic and clinical characteristics, showed that age ⩾60 years decreased the odds for ILI by 52% and 81% during the seasonal and A(H1N1)pdm09 pandemic periods, respectively. Being vaccinated decreased the odds of ILI for seasonal influenza by 32%, while suffering from the comorbidities other than lung or cardiovascular diseases doubled the odds of ILI during the A(H1N1)pdm09 pandemic.

scholarly journals Seroprevalence of anti-SARS-CoV-2 total antibody is higher in younger Austrian blood donors

Infection ◽  
2021 ◽  
Author(s):  
Lisa Weidner ◽  
Verena Nunhofer ◽  
Christof Jungbauer ◽  
Alexandra Domnica Hoeggerl ◽  
Lydia Grüner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Blood Group ◽  
Blood Donors ◽  
Blood Donation ◽  
Adult Population ◽  
Multiple Logistic Regression ◽  
Federal States ◽  
Testing Strategies ◽  
The Impact ◽  
Time Point

Abstract Purpose Frequently the infection with coronavirus 2 (SARS-CoV-2) can be asymptomatic or provoke only mild symptoms. These cases often remain unnoticed, so it is difficult to estimate the actual numbers of infections. Aim of this study was to determine the seroprevalence of anti-SARS-CoV-2 total antibody in Austrian blood donors. Methods 20,228 blood donors aged between 18 and 72 years resident in four Austrian federal states were screened for anti-SARS-CoV-2 total antibody between 5th of June and 4th of December 2020. To evaluate the impact of sex, age, AB0-blood group and donation period on the anti-SARS-CoV-2 seroprevalence, multiple logistic regression was done. Results Our data reveal an anti-SARS-CoV-2 seroprevalence of 2.5% overall, significantly depending on the time point of blood donation: after the first Austrian lockdown the seroprevalence was lower compared to the following months, when the rate was constantly rising. While younger blood donors showed significantly higher seroprevalence, no differences were found concerning sex or AB0 blood group. Conclusion Broad testing strategies are required to better determine the number of SARS-CoV-2 infections. Screening blood donors as a representative group for the adult population could be a valid tool to determine the number of recorded and unrecorded cases of SARS-CoV-2 infection.

Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

1980 ◽  
Vol 19 (01) ◽  
pp. 42-49 ◽  
Author(s):  
B. W. Brown ◽  
C. Engelhard ◽  
J. Haipern ◽  
J. F. Fries ◽  
L. S. Coles
Keyword(s):  
Logistic Regression ◽  
Predictor Variable ◽  
Clinical Problem ◽  
Relevant Information ◽  
Stepwise Logistic Regression ◽  
Multiple Logistic Regression ◽  
Binary Outcome ◽  
Medical Problems ◽  
Valuable Predictor ◽  
Data Banks

In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

scholarly journals Promoting Sustainable Mobility: A Perspective from Car and Public Transport Users

2021 ◽  
Vol 18 (9) ◽  
pp. 4715
Author(s):  
Audrius Dėdelė ◽  
Auksė Miškinytė
Keyword(s):  
Public Transport ◽  
Adult Population ◽  
Individual Characteristics ◽  
Urban Mobility ◽  
Sustainable Mobility ◽  
Bicycle Safety ◽  
Key Factor ◽  
The Individual ◽  
Significant Factors

Sustainable mobility is becoming a key factor in improving the quality of life of the residents and increasing physical activity (PA) levels. The current situation of sustainable mobility and its analysis is a first step in understanding the factors that would encourage residents to discover and choose alternative modes of travel. The present study examined the factors that encourage the choice of active modes of travel among urban adult population. Walking and cycling were analyzed as the most sustainable forms of urban mobility from the perspective of car and public transport (PT) users. Total of 902 subjects aged 18 years or older were analyzed in the study to assess commuting habits in Kaunas city, Lithuania. The majority (61.1%) of the respondents used a passenger vehicle, 28.2% used PT, and only 13.5% used active modes of travel. The results showed that safer pedestrian crossings, and comfortable paths were the most significant factors that encourage walking. A wider cycling network, and bicycle safety were the most important incentives for the promotion of cycling. Our findings show that the main factors encouraging walking and cycling among car and PT users are similar, however, the individual characteristics that determine the choice of these factors vary significantly.

scholarly journals Analysing the impact of the COVID-19 outbreak on everyday travel behaviour in Germany and potential implications for future travel patterns

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Viktoriya Kolarova ◽  
Christine Eisenmann ◽  
Claudia Nobis ◽  
Christian Winkler ◽  
Barbara Lenz
Keyword(s):  
Public Transport ◽  
Online Survey ◽  
Adult Population ◽  
Activity Patterns ◽  
Age Groups ◽  
Travel Behaviour ◽  
German Population ◽  
Travel Patterns ◽  
Home Office ◽  
The Impact

Abstract Introduction The global Coronavirus (COVID-19) pandemic is having a great impact on all areas of the everyday life, including travel behaviour. Various measures that focus on restricting social contacts have been implemented in order to reduce the spread of the virus. Understanding how daily activities and travel behaviour change during such global crisis and the reasons behind is crucial for developing suitable strategies for similar future events and analysing potential mid- and long-term impacts. Methods In order to provide empirical insights into changes in travel behaviour during the first Coronavirus-related lockdown in 2020 for Germany, an online survey with a relative representative sample for the German population was conducted a week after the start of the nationwide contact ban. The data was analysed performing descriptive and inferential statistical analyses. Results and Discussion The results suggest in general an increase in car use and decrease in public transport use as well as more negative perception of public transport as a transport alternative during the pandemic. Regarding activity-related travel patterns, the findings show firstly, that the majority of people go less frequent shopping; simultaneously, an increase in online shopping can be seen and characteristics of this group were analysed. Secondly, half of the adult population still left their home for leisure or to run errands; young adults were more active than all other age groups. Thirdly, the majority of the working population still went to work; one out of four people worked in home-office. Lastly, potential implications for travel behaviour and activity patterns as well as policy measures are discussed.

Experimental study on the factors affecting squeak noise occurrence in automotive suspension bushings

2021 ◽  
pp. 095440702110241
Author(s):  
Byunghyun Kang ◽  
Cheol Choi ◽  
Daeun Sung ◽  
Seongho Yoon ◽  
Byoung-Ho Choi
Keyword(s):  
Neural Network ◽  
Logistic Regression ◽  
Influencing Factors ◽  
Frictional Force ◽  
Prediction Models ◽  
Statistical Tests ◽  
Network Models ◽  
Multiple Logistic Regression ◽  
Neural Network Models ◽  
Automotive Suspension

In this study, friction tests are performed, via a custom-built friction tester, on specimens of natural rubber used in automotive suspension bushings. By analyzing the problematic suspension bushings, the eleven candidate factors that influence squeak noise are selected: surface lubrication, hardness, vulcanization condition, surface texture, additive content, sample thickness, thermal aging, temperature, surface moisture, friction speed, and normal force. Through friction tests, the changes are investigated in frictional force and squeak noise occurrence according to various levels of the influencing factors. The degree of correlation between frictional force and squeak noise occurrence with the factors is determined through statistical tests, and the relationship between frictional force and squeak noise occurrence based on the test results is discussed. Squeak noise prediction models are constructed by considering the interactions among the influencing factors through both multiple logistic regression and neural network analysis. The accuracies of the two prediction models are evaluated by comparing predicted and measured results. The accuracies of the multiple logistic regression and neural network models in predicting the occurrence of squeak noise are 88.2% and 87.2%, respectively.

Association between Procalcitonin and Acute Kidney Injury in Patients with Bacterial Septic Shock

2021 ◽  
pp. 1-10
Author(s):  
Guang Fu ◽  
Hai-chao Zhan ◽  
Hao-li Li ◽  
Jun-fu Lu ◽  
Yan-hong Chen ◽  
...  
Keyword(s):  
Septic Shock ◽  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Piecewise Linear ◽  
Kidney Injury ◽  
Multiple Logistic Regression ◽  
Primary Analysis ◽  
Female Patients ◽  
Potential Biomarker ◽  
The Relationship

Objective: The objective of this study was to assess the relationship between serum procalcitonin (PCT) and acute kidney injury (AKI) induced by bacterial septic shock. Methods: A retrospective study was designed which included patients who were admitted to the ICU from January 2015 to October 2018. Multiple logistic regression and receiver operating characteristic (ROC) as well as smooth curve fitting analysis were used to assess the relationship between the PCT level and AKI. Results: Of the 1,631 patients screened, 157 patients were included in the primary analysis in which 84 (53.5%) patients were with AKI. Multiple logistic regression results showed that PCT (odds ratio [OR] = 1.017, 95% confidence interval [CI] 1.009–1.025, p < 0.001) was associated with AKI induced by septic shock. The ROC analysis showed that the cutoff point for PCT to predict AKI development was 14 ng/mL, with a sensitivity of 63% and specificity 67%. Specifically, in multivariate piecewise linear regression, the occurrence of AKI decreased with the elevation of PCT when PCT was between 25 ng/mL and 120 ng/mL (OR 0.963, 95% CI 0.929–0.999; p = 0.042). The AKI increased with the elevation of PCT when PCT was either <25 ng/mL (OR 1.077, 95% CI 1.022–1.136; p = 0.006) or >120 ng/mL (OR 1.042, 95% CI 1.009–1.076; p = 0.013). Moreover, the PCT level was significantly higher in the AKI group only in female patients aged ≤75 years (p = 0.001). Conclusions: Our data revealed a nonlinear relationship between PCT and AKI in septic shock patients, and PCT could be used as a potential biomarker of AKI in female patients younger than 75 years with bacterial septic shock.

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