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      Predictors of current tobacco smoking by adolescents in Nigeria: Interaction between school location and socioeconomic status

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          Abstract

          INTRODUCTION

          Tobacco smoking is the largest preventable cause of global mortality, with its prevalence increasing in Sub-Saharan Africa, particularly among adolescents. We sought to determine the factors associated with tobacco smoking among Nigerian school adolescents and investigate the interaction between school location and socioeconomic status (SES).

          METHODS

          Using a cross-sectional study design, 4332 eighth to tenth grade students in rural and urban secondary schools in Enugu State, Nigeria, were selected by stratified two-stage cluster sampling. We collected data using a modified Global Youth Tobacco Survey (GYTS) Core Questionnaire. Outcome measures were current smoking of cigarettes and other smoked tobacco. Multilevel mixed effects logistic regression models were used to determine factors associated with current tobacco smoking and were considered statistically significant at p<0.05.

          RESULTS

          Prevalences of current smoking of cigarettes and other smoked tobacco were 13.3% (95% CI: 11.3–15.7) and 5.8% (95% CI: 4.6–7.2), respectively. Possession of higher weekly allowance, exposure to secondhand smoke or tobacco advertisements, having smoking parents, friends or classmates who smoke, and sale of cigarettes near school, were positively associated with current smoking of tobacco. Female sex, having both parents employed and being exposed to tobacco teaching in school were negatively associated with current cigarette smoking while increasing age and high father’s SES were negatively associated with current smoking of other tobacco products. There was an interaction between school location and father’s SES in the association with cigarette smoking. The higher odds of smoking in rural versus urban schools were much higher for students with fathers of high SES compared to low SES. In rural schools, high SES was associated with higher odds of smoking, but in urban schools low SES was associated with higher odds of smoking. CONCLUSIONS Environmental factors are associated with adolescent tobacco smoking. Tobacco control programs should use targeted strategies that vary depending on the local context.

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          Most cited references36

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          Purposeful selection of variables in logistic regression

          Background The main problem in many model-building situations is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a variable in the model might be based on the clinical or statistical significance. There are several variable selection algorithms in existence. Those methods are mechanical and as such carry some limitations. Hosmer and Lemeshow describe a purposeful selection of covariates within which an analyst makes a variable selection decision at each step of the modeling process. Methods In this paper we introduce an algorithm which automates that process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS PROC LOGISTIC: FORWARD, BACKWARD, and STEPWISE. Results We show that the advantage of this approach is when the analyst is interested in risk factor modeling and not just prediction. In addition to significant covariates, this variable selection procedure has the capability of retaining important confounding variables, resulting potentially in a slightly richer model. Application of the macro is further illustrated with the Hosmer and Lemeshow Worchester Heart Attack Study (WHAS) data. Conclusion If an analyst is in need of an algorithm that will help guide the retention of significant covariates as well as confounding ones they should consider this macro as an alternative tool.
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            Adolescent cortical development: a critical period of vulnerability for addiction.

            Cortical growth and remodeling continues from birth through youth and adolescence to stable adult levels changing slowly into senescence. There are critical periods of cortical development when specific experiences drive major synaptic rearrangements and learning that only occur during the critical period. For example, visual cortex is characterized by a critical period of plasticity involved in establishing visual acuity. Adolescence is defined by characteristic behaviors that include high levels of risk taking, exploration, novelty and sensation seeking, social interaction and play behaviors. In addition, adolescence is the final period of development of the adult during which talents, reasoning and complex adult behaviors mature. This maturation of behaviors corresponds with periods of marked changes in neurogenesis, cortical synaptic remodeling, neurotransmitter receptors and transporters, as well as major changes in hormones. Frontal cortical development is later in adolescence and likely contributes to refinement of reasoning, goal and priority setting, impulse control and evaluating long and short term rewards. Adolescent humans have high levels of binge drinking and experimentation with other drugs. This review presents findings supporting adolescence as a critical period of cortical development important for establishing life long adult characteristics that are disrupted by alcohol and drug use.
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              Reliability of the 1999 youth risk behavior survey questionnaire.

              To assess the test-retest reliability of the 1999 Youth Risk Behavior Survey (YRBS) questionnaire. A sample of 4,619 male and female high school students from white, black, Hispanic, and other racial/ethnic groups completed the YRBS questionnaire on two occasions approximately two weeks apart. The questionnaire assesses a broad range of health risk behaviors. This study used a protocol that maintained anonymity yet allowed matching of Time-1 and Time-2 responses. The authors computed a kappa statistic for the 72 items measuring health risk behaviors, and compared group prevalence estimates at the two testing occasions. Kappas ranged from 23.6% to 90.5%, with a mean of 60.7% and a median of 60.0%. Kappas did not differ by gender, grade, or race/ethnicity of the respondent. About one in five items (22.2%) had significantly different prevalence estimates at Time 1 vs. Time 2. Ten items, or 13.9%, had both kappas below 61% and significantly different Time-1 and Time-2 prevalence estimates. Overall, students appeared to report health risk behaviors reliably over time, but several items need to be examined further to determine whether they should be revised or deleted in future versions of the YRBS.
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                Author and article information

                Journal
                Tob Induc Dis
                Tob Induc Dis
                TID
                Tobacco Induced Diseases
                European Publishing on behalf of the International Society for the Prevention of Tobacco Induced Diseases (ISPTID)
                2070-7266
                1617-9625
                03 March 2020
                2020
                : 18
                : 13
                Affiliations
                [1 ]Department of Community Medicine, University of Nigeria, Enugu, Nigeria
                [2 ]Department of Community Medicine, University of Nigeria Teaching Hospital, Enugu, Nigeria
                [3 ]Department of Public Health Sciences, University of Rochester, Rochester, United States
                [4 ]Institute of Maternal and Child Health, University of Nigeria, Enugu, Nigeria
                Author notes
                CORRESPONDENCE TO Ijeoma U. Itanyi. Department of Community Medicine, Faculty of Medical Sciences, College of Medicine, University of Nigeria, Nsukka, Ituku-Ozalla Campus, Enugu, Nigeria. E-mail: ijeoma.itanyi@ 123456unn.edu.ng ORCID ID: https://orcid.org/0000-0002-4958-6319
                Article
                13
                10.18332/tid/117959
                7067232
                32180690
                3e169abd-e03e-48e4-8d27-0eaa15575267
                © 2020 Itanyi I.U. et al.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License.

                History
                : 17 July 2019
                : 23 January 2020
                : 05 February 2020
                Categories
                Research Paper

                Respiratory medicine
                tobacco smoking,adolescent,predictors,interaction,nigeria
                Respiratory medicine
                tobacco smoking, adolescent, predictors, interaction, nigeria

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