scholarly journals Prevalence of cigarette smoking and its predictors among school going adolescents of North India

2014 ◽  
Vol 03 (04) ◽  
pp. 193-195 ◽  
Author(s):  
Durgesh Thakur ◽  
Anmol Gupta ◽  
Anita Thakur ◽  
Salig Ram Mazta ◽  
Deepak Sharma
Keyword(s):  
Cigarette Smoking ◽  
Smoking Behavior ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Free Time ◽  
North India ◽  
Binary Logistic Regression Model ◽  
Current Cigarette Smoking ◽  
Cross Sectional ◽  
Current Cigarette

Abstract Background: Cigarettes smoking is a common mode of consuming tobacco in India. This habit usually starts in adolescence and tracks across the life course. Interventions like building decision making skills and resisting negative influences are effective in reducing the initiation and level of tobacco use. Aims and Objectives: The purpose of this study was to assess the prevalence of adolescent current cigarette smoking behavior and to investigate the individual and social factors, which influence them both to and not to smoke. Methodology: A cross-sectional study was carried out among school going adolescents in Shimla town of North India. After obtaining their written informed consent, a questionnaire was administered. Results: The overall prevalence of current cigarette smoking was 11.8%. The binary logistic regression model revealed that parents′ and peers′ smoking behavior influence adolescent smoking behavior. Individual self-harm tendency also significantly predicted cigarette smoking behavior. Parental active participation in keeping a track of their children′s free time activities predicted to protect adolescents from taking this habit. Conclusion: Our research lends support to the need for intervention on restricting adolescents from taking up this habit and becoming another tobacco industries′ addicted customer. Parents who smoke should quit this habit, which will not only restore their own health, but also protect their children. All parents should be counseled to carefully observe their children′s free time activities.

Determinants of cigarette smoking among school adolescents on the island of Java, Indonesia

2017 ◽  
Vol 29 (2) ◽  
Author(s):  
Mouhamad Bigwanto ◽  
Aroonsri Mongkolcharti ◽  
Karl Peltzer ◽  
Orapin Laosee
Keyword(s):  
Cigarette Smoking ◽  
Self Efficacy ◽  
Smoking Behavior ◽  
Cross Sectional Study ◽  
Integrated Model ◽  
Cluster Sampling ◽  
Current Cigarette Smoking ◽  
Cross Sectional ◽  
Multi Stage ◽  
Current Cigarette

Abstract Background: The Integrated Model of Change has successfully explained the behavior change process. Cigarette smoking is a social phenomenon, which needs to be understood for devising effective preventive strategies. Objectives: The study aims to apply the Integrated Model of Change to determine predictive factors of cigarette smoking behavior among school adolescents in Indonesia. Methods: A school-based cross-sectional study was designed to collect data in Banten, Indonesia. A total of 698 students from eight high schools were recruited by multi-stage cluster sampling. The association between cigarette smoking and the independent variables was examined by multiple logistic regressions. Results: The majority of respondents (86.4%) were between the ages of 15 and 17 years (Mean=16.4 years; SD=1.01). Approximately half (48.8%) of the students ever tried a cigarette while 29.6% were current smokers. Curiosity was reported as the main reason for experimenting with cigarettes (32%). The significant factors regarding current cigarette smoking were attitude [adjusted odds ratio (AOR)=2.68], social norms (AOR=12.80), self-efficacy (AOR=15.85), and accessibility (AOR=4.39). Conclusion: The study revealed social influence and self-efficacy that were strongly associated with cigarette smoking can help authorities in guiding possible intervention programs for school adolescents.

scholarly journals Smoking characteristics and lung functions among university athletes

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Narongkorn Saiphoklang ◽  
Orapan Poachanukoon ◽  
Suchada Soorapan
Keyword(s):  
Cigarette Smoking ◽  
Smoking Prevalence ◽  
Cross Sectional Study ◽  
Negative Effects ◽  
Current Cigarette Smoking ◽  
Cross Sectional ◽  
Lung Functions ◽  
Current Cigarette ◽  
Exhaled Carbon Monoxide ◽  
University Athletes

AbstractCigarette smoking has negative effects on the respiratory system, particularly pulmonary functions. This study aimed to determine smoking prevalence and characteristics among university athletes. We conducted a cross-sectional study of Thammasat University athletes in Thailand from July to October 2018. Demographic and smoking data were recorded. Exhaled carbon monoxide (CO) levels and lung function data were analysed. A total of 433 subjects (56% men) were included. Mean age was 19.8 ± 1.3 years. Asthma was reported in 5.5%. The prevalence of current cigarette smoking was 23.8%. Tobacco use was 3.0 ± 3.2 cigarettes per day. The Fagerstrom score for nicotine dependence was 0.76 ± 1.47. Compared to non-smokers, smokers were predominately males (70.6% vs 29.4%, P < 0.001), had higher exhaled CO levels (3.75 ± 3.08 ppm vs 2.18 ± 0.73 ppm, P < 0.001), higher FVC (89.65 ± 17.61% vs 83.22 ± 15.72%, P = 0.001), higher FEV1 (92.60 ± 15.36% vs 87.77 ± 11.23%, P = 0.002), but lower FEV1/FVC (78.21 ± 5.38% vs 79.70 ± 5.60%, P = 0.015). Moreover, athletes who smoke, were more likely to: drink alcohol, have a family member who smokes, have a friend who smokes or have a university instructor who smokes. In conclusion, smoking prevalence among university athletes was relatively high, although low nicotine addiction level and good lung functions were found. Home and institute environments had important influences on cigarette use in students.Trial registration: TCTR20180917001

scholarly journals Comparing the Characteristics of Cigarette Smoking and e-Cigarette and IQOS Use among Adolescents in Taiwan

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Yue-Chune Lee ◽  
Li-Chuan Chang ◽  
Chieh Hsu ◽  
Pei-Ching Chen
Keyword(s):  
Socioeconomic Status ◽  
Cigarette Smoking ◽  
Educational Level ◽  
Smoking Status ◽  
Smoking Behavior ◽  
Tobacco Product ◽  
Current Cigarette Smoking ◽  
Global Youth Tobacco Survey ◽  
Cross Sectional ◽  
Current Cigarette

Objectives. Our objective in this study was to identify the risk factors for cigarette, e-cigarette, and IQOS use among adolescents in Taiwan, with a particular focus on socioeconomic status, smoking status of parents and peers, cigarette promotions, and anti-tobacco campaigns. Methods. Data were obtained from the 2018 version of the annual cross-sectional Taiwan Global Youth Tobacco Survey, which is used to monitor tobacco use among Taiwanese adolescents in junior and senior high schools. The dependent variables in the study were “current cigarette smoking,” “current use of e-cigarettes,” and “current use of IQOS devices” (i.e., during the 30 days prior to survey completion). Independent variables included gender, school grade, monthly income/allowance, educational level of parents, smoking status of parents, smoking status of close friends, access to free cigarettes, exposure to cigarette advertisements, and attendance at anti-tobacco courses. Logistic regression was used in the identification of factors correlated with the current use of cigarettes, e-cigarettes, or IQOS. Results. We determined that 5.65% of the adolescents in the study were currently using cigarettes, 2.74% were currently using e-cigarettes, and 2.33% were currently using IQOS. Our analysis revealed a number of factors that have a bearing on smoking behavior, including gender, monthly allowance, educational level of parents, smoking status of parents and close friends, access to free cigarettes, and exposure to cigarette advertisements. Conclusions. The tobacco product that was most widely used by adolescents was cigarettes, followed by e-cigarettes and IQOS. The socioeconomic status, smoking status of parents/close friends, and access to cigarettes were all identified as important factors related to the current use of cigarettes, e-cigarettes, and IQOS by adolescents.

scholarly journals Predicting Prevention of Cigarette Smoking in Youth: Using Multi-Theory Model (MTM)

2020 ◽  
Author(s):  
Hamid Abasi ◽  
Zahra Sadat Asadi ◽  
Naser Mohammad gholi Mezerji
Keyword(s):  
Logistic Regression ◽  
Cigarette Smoking ◽  
Simple Random Sampling ◽  
Cross Sectional Study ◽  
Theory Model ◽  
Current Cigarette Smoking ◽  
Cross Sectional ◽  
Prevention Interventions ◽  
Current Cigarette ◽  
Military Services

Abstract Background: Cigarette smoking (CS) is the most important cause of death and disability in the world and is a complex behavior that is affected by various factors. This study was aimed to test the ability of MTM to predict preventing CS in youth.Methods: In this cross-sectional study, 230 youth who were volunteer to do military services as a soldier were selected by simple random sampling in 2019, western Iran. Data collection were performed by using questionnaire demographic characteristics and MTM constructs of CS. The obtained data were analyzed using descriptive statistics, logistic regression, and Hosmer–Lemeshow test in SPSS 20 software.Results: In this study, the Mean (± SD) age of the participants was 21.13 (±0.89). The prevalence of current cigarette smoking (CCS) and ever cigarette smoking (ECS) was 12.2% and 23%, respectively. The results of the logistic regression test showed that ECS (p< 0.001) and having a family member smoker (p=0.026) were predictor factors for CCS. Sustenance of preventing CS behavior was predicted by constructs of emotional transformation (p=0/006), practice for change (p=0=022), and changes in the social environment (p< 0.001).Conclusions: MTM shows that it is a reliable and useful theory in the sustenance of preventing CS behavior in youth who volunteer to do military services as soldiers. Therefore, this robust theory should be tested in designing, implementing, and evaluating of CS prevention interventions.

scholarly journals Smoking behavior of adolescents and their view towards government's ban on smoking in public places in Kathmandu

2015 ◽  
Vol 3 (2) ◽  
pp. 94-100
Author(s):  
S Dahal ◽  
RK Subedi ◽  
S Maharjan ◽  
J Maharjan
Keyword(s):  
Cigarette Smoking ◽  
Smoking Behavior ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Control Programs ◽  
Adolescent Students ◽  
Smoking Control ◽  
Questionnaire Method

Background: Several studies have reported that different forms of tobacco use are high in Nepal. However, information about factors affecting the cigarette smoking behavior of adolescents is inadequate. The objective of this study was to explore the cigarette smoking behavior of adolescents and to determine its association with their views towards cigarette smoking.Methods: A cross-sectional study was conducted among 394 adolescent students by using questionnaire method in 3 randomly selected colleges of Kathmandu district, Nepal. Data were analyzed by using bivariate and binary logistic regression analysis.Results: The study found that 22% of the students were ever smokers. Higher percentage of students receiving more amount of pocket money, having poor academic performance, having frequent dispute with teachers, having alcohol using and smoker family members were ever smokers. Multivariate analysis showed that students were more likely to be current smokers if they have positive views towards smoking and were less likely to be current smokers if they have negative view towards smoking (p<0.01).Conclusion: Reasons for smoking are many that create challenges for smoking control programs. Changing the views and imagery of adolescents’ towards cigarette smoking should also be considered while designing such programs.Nepal Journal of Medical Sciences Vol.3(2) 2014: 94-100

What Makes a Tweet Fly? Analysis of Twitter Messaging at Four Infection Control Conferences

2017 ◽  
Vol 38 (11) ◽  
pp. 1271-1276 ◽  
Author(s):  
Brett G. Mitchell ◽  
Philip L. Russo ◽  
Jonathan A. Otter ◽  
Martin A. Kiernan ◽  
Landon Aveling
Keyword(s):  
Network Analysis ◽  
Infection Control ◽  
Infection Prevention ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Infection Prevention And Control ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Activity Networks ◽  
The Uk

OBJECTIVETo examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences.DESIGNA cross-sectional study.METHODSAn independent company was commissioned to undertake a Twitter ‘trawl’ each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of ‘retweets.’RESULTSIn total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9–2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7–2.4) and the media (OR, 1.8; 95% CI, 1.6–2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05–0.08).CONCLUSIONTwitter is a useful tool for information sharing and networking at infection control conferences.Infect Control Hosp Epidemiol 2017;38:1271–1276

scholarly journals Association between Free Sugars Intake and Excessive Daytime Sleepiness among Chinese Adolescents

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 3959
Author(s):  
Yue Xi ◽  
Qian Lin ◽  
Qiping Yang ◽  
Fang Li ◽  
Hanmei Liu ◽  
...  
Keyword(s):  
Excessive Daytime Sleepiness ◽  
Daytime Sleepiness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Chinese Adolescents ◽  
Binary Logistic Regression Model ◽  
School Students ◽  
Online Questionnaire ◽  
Cross Sectional ◽  
Free Sugars

This study aimed to investigate the prevalence of excessive daytime sleepiness (EDS) and explore the association between free sugars intake and EDS. In this cross-sectional study, a total of 1517 middle school students (808 boys and 707 girls) aged 12~14 years were recruited. The study was conducted in Changsha city, China. Adolescents completed an online questionnaire, including the Epworth Sleepiness Scale (ESS), sleep characteristics, a 12-item Food Frequency Questionnaire (FFQ), and other self-reported information. The ESS score ≥ ten was defined as EDS. The anthropometric indices, including height, weight, and waist circumference, were measured and recorded by uniformly trained assistants. Statistical analyses included the Chi-square test and binary logistic regression model. The mean ESS score and free sugars consumption were 6.8 ± 3.9 points and 53.1 ± 44.7 g/d, respectively. The prevalence of EDS among adolescents was 22.5%, and more girls than boys had EDS (26.1% vs. 19.4%, p < 0.05). An exceeded free sugars intake was positively associated with EDS, with the adjusted Odds Ratio (OR) with its 95% Confident Interval (95% CI) of 1.366 (1.060~1.761, p < 0.05). EDS and excessive consumption of free sugars are commonly found among Chinese adolescents. Further studies are needed to confirm whether free sugars restriction can be meaningful to improve daytime drowsiness in those with EDS.

scholarly journals The Practices of Anaesthesiologists in the Management of Patients with Sickle Cell Disease: Empirical Evidence from Cameroon

Healthcare ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1617
Author(s):  
Dominique Djomo Tamchom ◽  
Aristide Kuitchet ◽  
Raymond Ndikontar ◽  
Serge Nga Nomo ◽  
Hermine Fouda ◽  
...  
Keyword(s):  
Sickle Cell Disease ◽  
Sickle Cell ◽  
Perioperative Management ◽  
Treatment Guideline ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Cell Disease ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Elective Surgical Procedures

Patients with sickle cell disease are more likely to undergo surgery during their lifetime, especially given the numerous complications they may develop. There is a paucity of data concerning the management of patients with sickle cell disease by anaesthesiologists, especially in Africa. This study aimed to describe the practices of anaesthesiologists in Cameroon concerning the perioperative management of patients with sickle cell disease. A cross-sectional study was carried out over four months and involved 35 out 47 anaesthesiologists working in hospitals across the country, who were invited to fill a data collection form after giving their informed consent. The data were analysed using descriptive statistics and a binary logistic regression model. Among the 35 anaesthesiologists included in the study, most (29 (82.9%)) had managed patients with sickle cell disease for both emergency and elective surgical procedures. Most of them had never asked for a haematology consultation before surgery. Most participants (26 (74.3%)) admitted to having carried out simple blood transfusions, while 4 (11.4%) carried out exchange transfusions. The haemoglobin thresholds for transfusion varied from one practitioner to another, between < 6 g/dl and < 9 g/dl. Only 6 (17.1%) anaesthesiologists had a treatment guideline for the management of patients with sickle cell disease in the hospitals where they practiced. Only 9 (25.7%) prescribed a search for irregular agglutinins. The percentage of haemoglobin S before surgery was always available for 5 (14.3%) of the participants. The coefficient (0.06) of the occurrence of a haematology consultation before surgery had a significant influence on the probability of management of post-operative complications (coefficient 0.06, 10% level of probability). This study highlights the fact that practices in the perioperative management of patients with sickle cell disease in Cameroon vary greatly from one anaesthesiologist to another. We disclosed major differences in the current recommendations, which support the fact that even in Sub-Saharan countries, guidelines applicable to the local settings should be published.

scholarly journals A predictive model for early diagnosis of keratoconus

2020 ◽  
Author(s):  
GRACIA CASTRO-LUNA ◽  
ANTONIO PÉREZ-RUEDA
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Early Stage ◽  
Corneal Thickness ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Bivariate Analysis ◽  
Diagnostic Model ◽  
Binary Logistic Regression Model ◽  
Cross Sectional

Abstract Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore, to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 early-stage keratoconus and 83 established keratoconus. The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of early-stage keratoconus was calculated with the statistically significant variables Results: Statistically significant differences were observed when comparing normal corneas with early-stage keratoconus/ in variables of the vertical asymmetry to 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. The model properly diagnosed 92% of cases with a sensitivity of 97.59%, specificity 98.78%, accuracy 98.18% and precision 98.78%Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90º and the posterior coma to 90º.

scholarly journals A model of visual limitation in patients with keratoconus

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Antonio Pérez-Rueda ◽  
Gracia Castro-Luna
Keyword(s):  
Visual Acuity ◽  
Logistic Regression ◽  
Operating Characteristic ◽  
Spherical Aberration ◽  
Area Under The Curve ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Corrected Visual Acuity

Abstract This paper aims to calculate a relevance model of visual limitation (V.L.) in keratoconus patients based on refractive and topographic parameters. A cross-sectional study was carried out in Torrecárdenas Hospital, Almería, Spain, between February 2018 and July 2019. It included 250 keratoconus patients. Two groups were created according to a grading system of V.L. based on RETICS (Red Temática de Investigación Cooperativa en Salud) classification: keratoconus patients with no V.L. (best spectacle-corrected visual acuity (BSCVA) ≤ 0.05 logMAR) and keratoconus patients with V.L. (BSCVA > 0.05 logMAR). Correlations and a binary logistic regression were established. V.L. was correlated with maximum curvature (r = 0.649, p < 0.001) and root mean square higher-order aberrations (HOARMS) (r = 0.625, p < 0.001). Binary logistic regression included V.L. as the dependent variable and spherical equivalent, HOARMS, spherical aberration and interaction between the anterior and posterior vertical coma as independent variables. The model was a good fit. Area under the curve (A.U.C.) of receiver operating characteristic (R.O.C.) curve was 0.924, sensitivity 91.90%, specificity 83.60%, accuracy 88.94%; and precision 91.17%. Binary logistic regression model of V.L. is a good fit model to predict the early loss of visual acuity in keratoconus patients.

Sign in / Sign up

Export Citation Format

Share Document