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Prevalence and predictors of smoking in Butajira town, Ethiopia
Niels Schoenmaker, Jeroen Hermanides, Gail Davey
Ethiopian Journal of Health Development , 2005,
Abstract: Background: In order to design effective tobacco control policy in low income countries, it is essential to understand smoking prevalence and predictors. In Ethiopia, most of what is known on the prevalence of smoking comes from studies in larger towns. Little is known about predictors of smoking in any Ethiopian setting. Objectives: The analyses reported were designed to determine smoking prevalence and social factors associated with ever smoking in Butajira town. Methods: Cross-sectional study nested within a large questionnaire-based survey undertaken in Butajira, southern Ethiopia, between February and April 2003. Results: Prevalence data were available on 1895 individuals aged 15 years and over. 15.4% of men and 0.2% of women had ever smoked, and 11.8% and 0.2% respectively, were current smokers. Using logistic regression, male gender (p<0.001), increasing age (p<0.001), being a follower of Islam (p=0.002), and being in formal employment (p=0.033) were found to be independent predictors of ever smoking. Conclusions: Socio-demographic predictors of cigarette smoking in Butajira Ethiopia are different to those found in high income countries. The predictors found here suggest that increased taxation may be the most effective tobacco control measure in this low income country setting. Ethiopian Journal of Health Development Vol. 19(3) 2005: 182-187
Pakistan Journal of Statistics and Operation Research , 2011, DOI: 10.1234/pjsor.v7i2.185
Abstract: The literature related to skew-symmetric distribution have grown rapidly in recent years but at the moment no publication on its applications concerning the description of economically active data with this type of probability models. In this paper, we provided an extension to this skew-normal distribution, which is also part of the family of skewed class of normal but with additional shape parameters δ. Some properties of this distribution are presented and finally, we considered fitting it to economically active population data. The model exhibited a better behaviour when compared to normal and skew normal distributions.
Tobacco Smoking, Alcohol Drinking, Diabetes, Low Body Mass Index and the Risk of Self-Reported Symptoms of Active Tuberculosis: Individual Participant Data (IPD) Meta-Analyses of 72,684 Individuals in 14 High Tuberculosis Burden Countries  [PDF]
Jayadeep Patra, Prabhat Jha, Jürgen Rehm, Wilson Suraweera
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0096433
Abstract: Background The effects of multiple exposures on active tuberculosis (TB) are largely undetermined. We sought to establish a dose-response relationship for smoking, drinking, and body mass index (BMI) and to investigate the independent and joint effects of these and diabetes on the risk of self-reported symptoms of active TB disease. Methods and Findings We analyzed 14 national studies in 14 high TB-burden countries using self-reports of blood in cough/phlegm and cough lasting > = 3 weeks in the last year as the measures of symptoms of active TB. The random effect estimates of the relative risks (RR) between active TB and smoking, drinking, diabetes, and BMI<18.5 kg/m2 were reported for each gender. Floating absolute risks were used to examine dyads of exposure. Adjusted for age and education, the risks of active TB were significantly associated with diabetes and BMI<18.5 kg/m2 in both sexes, with ever drinking in men and with ever smoking in women. Stronger dose-response relationships were seen in women than in men for smoking amount, smoking duration and drinking amount but BMI<18.5 kg/m2 showed a stronger dose-response relationship in men. In men, the risks from joint exposures were statistically significant for diabetics with BMI<18.5 kg/m2 (RR = 6.4), diabetics who smoked (RR = 3.8), and diabetics who drank alcohol (RR = 3.2). The risks from joint risk factors were generally larger in women than in men, with statistically significant risks for diabetics with BMI<18.5 kg/m2 (RR = 10.0), diabetics who smoked (RR = 5.4) and women with BMI<18.5 kg/m2 who smoked (RR = 5.0). These risk factors account for 61% of male and 34% of female estimated TB incidents in these 14 countries. Conclusions Tobacco, alcohol, diabetes, and low BMI are significant individual risk factors but in combination are associated with triple or quadruple the risk of development of recent active TB. These risk factors might help to explain the wide variation in TB across countries.
Biomarkers of Induced Active and Passive Smoking Damage  [PDF]
Maura Lodovici,Elisabetta Bigagli
International Journal of Environmental Research and Public Health , 2009, DOI: 10.3390/ijerph6030874
Abstract: In addition to thewell-known link between smoking and lung cancer, large epidemiological studies have shown a relationship between smoking and cancers of the nose, oral cavity, oropharynx, larynx, esophagus, pancreas, bladder, kidney, stomach, liver, colon and cervix, as well as myeloid leukemia. Epidemiological evidence has reported a direct link between exposure of non-smokers to environmental tobacco smoke and disease, most notably, lung cancer. Much evidence demonstrates that carcinogenic-DNA adducts are useful markers of tobacco smoke exposure, providing an integrated measurement of carcinogen intake, metabolic activation, and delivery to the DNA in target tissues. Monitoring accessible surrogate tissues, such as white blood cells or bronchoalveolar lavage (BAL) cells, also provides a means of investigating passive and active tobacco exposure in healthy individuals and cancer patients. Levels of DNA adducts measured in many tissues of smokers are significantly higher than in non-smokers. While some studies have demonstrated an association between carcinogenic DNA adducts and cancer in current smokers, no association has been observed in ex or never smokers. The role of genetic susceptibility in the development of smoking related-cancer is essential. In order to establish whether smoking-related DNA adducts are biomarkers of tobacco smoke exposure and/or its carcinogenic activity we summarized all data that associated tobacco smoke exposure and smoking-related DNA adducts both in controls and/or in cancer cases and studies where the effect of genetic polymorphisms involved in the activation and deactivation of carcinogens were also evaluated. In the future we hope we will be able to screen for lung cancer susceptibility by using specific biomarkers and that subjects of compared groups can be stratified for multiple potential modulators of biomarkers, taking into account various confounding factors.
Predictors of Indoor Air Concentrations in Smoking and Non-Smoking Residences  [PDF]
Marie-Eve Héroux,Nina Clark,Keith Van Ryswyk,Ranjeeta Mallick,Nicolas L. Gilbert,Ian Harrison,Kathleen Rispler,Daniel Wang,Angelos Anastassopoulos,Mireille Guay,Morgan MacNeill,Amanda J. Wheeler
International Journal of Environmental Research and Public Health , 2010, DOI: 10.3390/ijerph7083080
Abstract: Indoor concentrations of air pollutants (benzene, toluene, formaldehyde, acetaldehyde, acrolein, nitrogen dioxide, particulate matter, elemental carbon and ozone) were measured in residences in Regina, Saskatchewan, Canada. Data were collected in 106 homes in winter and 111 homes in summer of 2007, with 71 homes participating in both seasons. In addition, data for relative humidity, temperature, air exchange rates, housing characteristics and occupants’ activities during sampling were collected. Multiple linear regression analysis was used to construct season-specific models for the air pollutants. Where smoking was a major contributor to indoor concentrations, separate models were constructed for all homes and for those homes with no cigarette smoke exposure. The housing characteristics and occupants’ activities investigated in this study explained between 11% and 53% of the variability in indoor air pollutant concentrations, with ventilation, age of home and attached garage being important predictors for many pollutants.
Waterpipe Smoking among Middle and High School Jordanian Students: Patterns and Predictors  [PDF]
Sukaina Alzyoud,Linda S. Weglicki,Khalid A. Kheirallah,Linda Haddad,Khalid A. Alhawamdeh
International Journal of Environmental Research and Public Health , 2013, DOI: 10.3390/ijerph10127068
Abstract: Despite the increase in attention to waterpipe tobacco smoking, the patterns and predictors of this method of tobacco use among Jordanian youth are not well known. The current study was conducted to assess the patterns and the predictors of waterpipe tobacco smoking among school aged students in one of Jordan’s Central Governorates. A cross-sectional survey was conducted to investigate the patterns and predictors of waterpipe tobacco smoking among youth (grades 6, 8, 10 and 12). Using a multistage random sampling more than 1,000 students was selected. Data were collected using the Arabic Youth Tobacco Use Composite Measure (YTUCM). Waterpipe smoking was assessed for “past 12 months”, “past month” and “past week”. Students’ ages ranged from 11 to 18 years, (mean age ± 14.7; SD ± 1.9 years). The percentage of girls who smoked waterpipe was greater for all frequencies of use than it was for boys. Age, gender, and belief that smoking makes more friends were predictors of smoking among study participants. This is the first known study to examine waterpipe smoking among youth aged 11 and 12. Our findings illustrate the need for public health campaigns to reach and educate youth, their families, teachers and school systems regarding the growing recognized health risks of waterpipe smoking.
Effect of smoking on active male smokers across various age groups
Abhinav,,Abhishek Chaudhary,R.Balaji Raja,Kantha D.Arunachalam
International Journal of Engineering Science and Technology , 2010,
Abstract: The most common form of smoking in the world is cigarette smoking, which is one of the leading causes of lung cancer, blood pressure, emphysema9, bronchitis, heart attack etc5… In the present study, Fourier-transform infrared spectroscopy was used for analysis of saliva sample for the detection of markers for smokers. The analysis included 7 individuals. The samples were classified as 2 samples from smokers of group 10-25, 2 samples from smokers of group 25-40, 1 sample from smokers of group 40-60 and 2 samples from smokers ofgroup 60 & above. Several interesting peaks have been identified as markers for smokers from saliva sample. Many peaks were significantly altered in absorption level of different age groups. The peaks at 754 cm-1, 1644 cm-1, 2136 cm-1, 3408 cm-1 were altered differently in different age groups as compared to non-smokers. Our study indicates that a stable marker was possible for active smokers by analysing the spectral graph obtained from the FTIR technique2. These parameters could be used for developing a spectral method of detection of active smokers along with predicting their duration of smoking by studying the effect of smoking in the different age groups.
Correspondence regarding "Effect of active smoking on the human bronchial epithelium transcriptome"
Scott D Zuyderduyn
BMC Genomics , 2009, DOI: 10.1186/1471-2164-10-82
Abstract: This correspondence raises questions about the validity of the approach used by the authors to analyze their data. The majority of the reported results suffer deficiencies due to the methods used. The most fundamental of these are explained in detail: biases introduced during data processing, lack of correction for multiple testing, and an incorrect use of clustering for gene discovery. A randomly generated "null" dataset is used to show the consequences of these shortcomings.Most of Chari et al.'s findings are consistent with what would be expected by chance alone. Although there is clear evidence of reversible changes in gene expression, the majority of those identified appear to be false positives. However, contrary to the authors' claims, no irreversible changes were identified. There is a broad consensus that genetic change due to smoking persists once an individual has quit smoking; unfortunately, this study lacks sufficient scientific rigour to support or refute this hypothesis or identify any specific candidate genes. The pitfalls of large-scale analysis, as exemplified here, may not be unique to Chari et al.I read with interest the recent work, published in BMC Genomics, entitled "Effect of active smoking on the human bronchial epithelium transcriptome" [1]. In this article, the authors present an analysis of gene expression profiles generated using serial analysis of gene expression (SAGE) [2]. The profiles were obtained from samples of the lung epithelium taken from individuals who have never smoked, had quit smoking, or are current smokers. The authors highlight the differences in gene expression between the three groups, with a particular focus on a substantial number of changes that appear to persist after an individual has stopped smoking. These results are intriguing, as they suggest that some etiology is permanently maintained after smoking cessation, that this manifests itself at the level of gene expression, and that such changes may contribute to
Prevalence and predictors of smoking in a mining town in Kitwe, Zambia: A 2011 population-based survey  [PDF]
Cosmas Zyaambo, Olusegun Babaniyi, Peter Songolo, Adamson S. Muula, Emmanuel Rudatsikira, Seter Siziya
Health (Health) , 2013, DOI: 10.4236/health.2013.56136

Smoking is one of the major preventable causes of death and non-communicable diseases which include hypertension, cardiovascular diseases and cancers. The aim of the study is to establish prevalence and predictors of smoking so that interventions specific to these communities can be executed to prevent smoking. A cross sectional study was conducted using a modified World Health Organizations Global Non Communicable Diseases (NCD) Surveillance Initiative NCD-STEPs 1 and 2. Multivariate logistic regression was used to examine the determinants of tobacco smoking. A total of 1627 individuals participated in the survey, of which 42.3% were males. About half of the participants were of age 25-34 years (56.0%), and 41.7% had attained secondary level of education. Overall, 8.7% of the participants (18.1% among males and 1.8% among females) currently smoked any tobacco product. Female respondents were 71% (AOR = 0.29, 95%CI [0.21, 0.39]) less likely to smoke cigarettes compared to male respondents. Compared to respondents who had no formal education, respondents who had attained primary level of education were 45% (AOR = 1.45, 95%CI [1.02, 2.08]) more likely to smoke, and those who attained college or university level of education were 57% (AOR = 0.43, 95%CI [0.28, 0.65]) less likely to smoke. Respondents who did not consume alcohol were 50% (AOR = 0.50, 95%CI [0.41, 0.61]) less likely to smoke compared to those who consumed alcohol. The study showed that sex, education, and alcohol consumption were independently associated with Smoking. These are the key determinants which should be considered when designing a health education and awareness campaign to the residents.

The Effects of Active and Passive Smoking upon Pregnancy and Fetus  [cached]
Ruhusen Kutlu
TAF Preventive Medicine Bulletin , 2008,
Abstract: Cigarette smoking is the most important avoidable cause of morbidity and premature death in the world. Maternal smoking during pregnancy is related not only to perinatal adverse events but also to important postnatal problems. Gestational maternal smoking is also associated with many developmental problems, including impaired fetal growth, which is largely assumed to be due to poor placental development, childhood respiratory ill-health, and abnormalities of the nervous system and cognition, as well as possible increased mortality risk for fetuses. Cigarette contains a complex mix of chemicals which can affect fetal development, including metals, nicotine and polycyclic aromatic hydrocarbons (PAH). Pregnant women who continue their smoking often give birth prematurely, the infants are often small for their gestational age, and they have more perinatal incidents. In addition to active smoking, to exposure the environmental tobacco smoke (ETS) is a major risk factor for respiratory disease in children. ETS exposure during pregnancy and the first years of life has been consistently found to have an impact on the respiratory system including symptoms such as wheezing, cough, bronchitis, RSV bronchiolitis, otitis media and asthma, but also on intrauterine growth, sudden infant death, behaviour and cognitive functioning. [TAF Prev Med Bull. 2008; 7(5): 445-448]
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