Risk Perception and Correlates of Tobacco Use among Young People Outside of Formal School Settings in Lagos State, Nigeria

Odukoya, OO,Dada, MR,Olubodun, T,Igwilo, UA,Ayo-Yusuf, OA Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.6

Background: Tobacco use among youth is a major public health problem. Youth outside of formal school settings are often understudied but may be at increased risk. Materials and Methods: A descriptive cross-sectional study was carried out among 326 young people aged 15-24 years in four randomly selected motor parks in Lagos state. Interviewer-administered questionnaires were used to collect data. Results: The mean age of the respondents was $21.0{\pm}2.3yrs$. Many 252 (77.3%) dropped out before the end of the third year of secondary schooling. The majority were aware that active (78.2%), and passive smoking (77.3%) are harmful to health. Nearly two-thirds of the respondents disagreed with an outright ban of cigarettes (63.2%) and restriction of cigarette sales to persons below 18 years (67.9%) while 254 (66.8%) supported a ban on tobacco smoking in enclosed public places. One hundred and fifty (46.0%) respondents had experimented with smoking of which 106 (32.5%) had progressed to become current smokers. Half of the current smokers, 54 (50.9%), felt the need for a cigarette first thing in the morning. A multivariate analysis for smoking initiation, showed that for every increasing year of age, respondents were 1.08 times more likely to have initiated cigarette smoking; males and respondents who lived alone or with peers were 2.34 times and 1.77 times more likely to have initiated smoking respectively; those who consume alcohol and marijuana were 7.27 and 1.89 times respectively more likely to have initiated smoking while those who consumed alcohol were 6.17 times more likely to be current smokers.

Determinants of Smoking Initiation and Susceptibility to Future Smoking among School-Going Adolescents in Lagos State, Nigeria

Odukoya, Oluwakemi Ololade,Odeyemi, Kofoworola Abimbola,Oyeyemi, Abisoye Sunday,Upadhyay, Ravi Prakash Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.3

Background: It is projected that low and middle-income countries will bear a major burden of tobacco related morbidity and mortality, yet, only limited information is available on the determinants of smoking initiation among youth in Africa. This study aimed to assess the determinants of smoking initiation and susceptibility to future smoking among a population of high school school students in Lagos, Nigeria. Materials and Methods: Baseline data from an intervention study designed to assess the effect of an anti-smoking awareness program on the knowledge, attitudes and practices of adolescents was analyzed. The survey was carried out in six randomly selected public and private secondary schools in local government areas in Lagos state, Nigeria. A total of 973 students completed self-administered questionnaires on smoking initiation, health related knowledge and attitudes towards smoking, susceptibility to future smoking and other factors associated with smoking. Results: Of the respondents, 9.7% had initiated smoking tobacco products with the predominant form being cigarettes (7.3%). Males (OR: 2.77, 95%CI: 1.65-4.66) and those with more pro-smoking attitudes (OR: 1.44, 95%CI: 1.34-1.54) were more likely to have initiated smoking. Those with parents and friends who are smokers were 3.47 (95%CI: 1.50-8.05) and 2.26 (95%CI: 1.27-4.01) times more likely to have initiated smoking. Non-smoking students, in privately owned schools (OR: 5.08), with friends who smoke (5.09), with lower knowledge (OR: 0.87) and more pro-smoking attitudes (OR 1.13) were more susceptible to future smoking. In addition, respondents who had been sent to purchase cigarettes by an older adult (OR: 3.68) were also more susceptible to future smoking. Conclusions: Being male and having parents who smoke are predictors of smoking initiation among these students. Consistent with findings in other countries, peers not only influence smoking initiation but also influence smoking susceptibility among youth in this African setting. Prevention programs designed to reduce tobacco use among in-school youth should take these factors into consideration. In line with the recommendations of article 16 of the WHO FCTC, efforts to enforce the ban on the sales of cigarettes to minors should be also emphasised.

Development and Comparison of Three Data Models for Predicting Diabetes Mellitus Using Risk Factors in a Nigerian Population

Oluwakemi Odukoya,Solomon Nwaneri,Ifedayo Odeniyi,Babatunde Akodu,Esther Oluwole,Gbenga Olorunfemi,Oluwatoyin Popoola,Akinniyi Osuntoki 대한의료정보학회 2022 Healthcare Informatics Research Vol.28 No.1

Objectives: This study developed and compared the performance of three widely used predictive models—logistic regression(LR), artificial neural network (ANN), and decision tree (DT)—to predict diabetes mellitus using the socio-demographic,lifestyle, and physical attributes of a population of Nigerians. Methods: We developed three predictive models using 10 inputvariables. Data preprocessing steps included the removal of missing values and outliers, min-max normalization, and featureextraction using principal component analysis. Data training and validation were accomplished using 10-fold cross-validation. Accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under thereceiver operating characteristic curve (AUROC) were used as performance evaluation metrics. Analysis and model developmentwere performed in R version 3.6.1. Results: The mean age of the participants was 50.52 ± 16.14 years. The classificationaccuracy, sensitivity, specificity, PPV, and NPV for LR were, respectively, 81.31%, 84.32%, 77.24%, 72.75%, and 82.49%. Those for ANN were 98.64%, 98.37%, 99.00%, 98.61%, and 98.83%, and those for DT were 99.05%, 99.76%, 98.08%, 98.77%,and 99.82%, respectively. The best-performing and poorest-performing classifiers were DT and LR, with 99.05% and 81.31%accuracy, respectively. Similarly, the DT algorithm achieved the best AUC value (0.992) compared to ANN (0.976) and LR(0.892). Conclusions: Our study demonstrated that DT, LR, and ANN models can be used effectively for the prediction ofdiabetes mellitus in the Nigerian population based on certain risk factors. An overall comparative analysis of the modelsshowed that the DT model performed better than LR and ANN.

Age of initiation, Determinants and Prevalence of Cigarette Smoking among Teenagers in Mushin Local Government Area of Lagos State, Nigeria

Abiola, AO,Balogun, OS,Odukoya, OO,Olatona, FA,Odugbemi, TO,Moronkola, RK,Solanke, AA,Akintunde, OJ,Fatoba, OO Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.3

Background: Cigarette smoking constitutes a major threat to the health and wellbeing of teenagers. While smoking has been on decline in the developed countries, the reverse is the case in developing countries. The aim of this study was to determine the age of initiation, determinants and prevalence of cigarette smoking among teenagers in Mushin Local Government Area of Lagos state, Nigeria. Materials and Methods: This was a descriptive cross-sectional study among 475 teenagers selected by multistage sampling. A pre-tested, structured, interviewer-administered questionnaire was used for data collection. The study was carried out in November, 2014. Results: Response rate was 84.6%. Mean age of the respondents was $16.4{\pm}1.65years$. Range and mean age of initiation of cigarette smoking were 7 to 17 years and $12.0{\pm}3.32years$ respectively. Teenagers who were above 15 years (OR:5.13, 95%CI: 0.87-30.26), males (OR:5.19, 95%CI: 1.57-17.18), married (OR:8.41, 95%CI: 1.04-63.35), had ${\leq}$primary school education(OR:4.31, 95%CI: 1.07-17.33), influenced by friends(OR:308.84, 95%CI:84.87-1123.81), and influenced by advertisements (OR:27.83, 95%CI: 3.92-197.64) were more likely to have initiated cigarette smoking. Furthermore, teenagers who were males (OR:12.77, 95%CI: 2.90-56.28), married (OR:19.24, 95%CI: 2.05-180.45), had ${\leq}$primary school education(OR:7.85, 95%CI: 2.37-26.01), influenced by friends(OR:28.56, 95%CI: 10.86-75.07), and influenced by advertisements (OR:5.95, 95%CI: 1.72-20.61) were more likely to be current cigarette smokers. In addition, 24.9% had initiated cigarette smoking while 14.7% were current smokers of cigarette. Conclusions: Mean age of initiation of cigarette smoking was $12.0{\pm}3.32years$. Determinants of cigarette smoking were age, gender, marital status, educational background, friends and advertisements. Life time prevalence of cigarette smoking was higher than prevalence of current cigarette smokers. Cigarette smoking reduction programs should take these factors into consideration.