Antismoking messages and current cigarette smoking status in Somaliland: results from the Global Youth Tobacco Survey 2004

The Republic of Somaliland is what was previously known as the Somaliland Protectorate under the British rule from 1884 to 1969. The country attained independence in June 1960 around the same time that Italian Somalia also achieved independence from Italy. On July 1st 1960 Somaliland joined the former Italian Somalia to form the Somali Republic. A civil war was fought from 1980 onwards resulting in the eventual collapse of the Somali Republic. Somaliland shares borders with Republic of Djibouti to the west, Federal Republic of Ethiopia to the south and, the Red Sea to the North and Somalia to the east.

This is a secondary analysis of data from the Somaliland GYTS conducted in 2004. The Somaliland GYTS was a school-based survey of students in public primary classes 6 to 8, and Secondary 1. These classes were selected because they contained the majority of 13 to 15 years old adolescents in Somaliland. A two-stage cluster sample design was used to produce representative data for all of Somaliland. At the first stage, schools were selected with probability proportional to enrollment size. At the second stage, classes were randomly selected and all students in selected classes were eligible to participate. The overall response rate was 82.9%; the school response rate was 88%, the student response rate was 94.2%. Altogether 1563 students participated in the Somaliland GYTS.

A GYTS questionnaire was administered to students in their classrooms during one subject session. Only students who were present on the day a particular school was visited participated in the study. Students who were eligible but absent were not followed up. Questionnaires were self-completed on computer scan able survey sheets.

Students were asked among others the following questions: During the past 30 days (one month), on how many days did you smoke cigarettes? Has anyone in your family discussed the harmful effects of smoking with you? During the past 30 days (one month), how many anti-smoking media messages (e.g., television, radio, billboards, posters, newspapers, magazines, movies) have you seen or heard? When you go to sports events, fairs, concerts, community events, or social gatherings, how often do you see anti-smoking messages? During this school year, were you taught in any of your classes about the effects of smoking like it makes your teeth yellow, causes wrinkles, or makes you smell bad?; During the past year, did any health professionals explain to you why smoking is dangerous to your health? During the past year, did any religious organization discourage young people of your age from smoking? Responses to the questions were all pre-coded. A comprehensive description of the GYTS methodology has been reported elsewhere [6‐8].

We obtained the data set from the CDC. Data were analyzed in SPSS 14.0 (Chicago, IL, United States of America). Current cigarette smoking was defined as having smoked a cigarette, even a single puff, within the last 30 days prior to the survey. A weighted analysis was conducted to obtain the prevalence of current cigarette smoking as well as other relevant characteristics. Associations between current smoking and categorical variables forming tables with two rows and two columns were assessed using the Yates corrected Chi-square test, and the Pearson Chi-square test was used for higher contingency tables. Age and sex adjusted odds ratios of current smoking and 95%CI were also obtained in a multivariate logistic regression analysis. A cut off point for statistical significance was set at the 5% level.

In order to understand and explain the results of the quantitative analysis in this study, three health behavior theories i.e. the Health Belief Model (HBM), the Knowledge, Attitude and Practice (KAP) model and the social cognitive theory (SCT) were used to explained the observed effect estimates with relation to explanatory variables [9‐13]. The SCT suggests that people's acquisition and maintenance of behavioral patterns is dependent on their own cognitive capacity, as well as on social-physical environment in which they are situated. The HBM on the other hand, promotes four constructs representing the perceived threat and net benefits: perceived susceptibility, perceived severity, perceived benefits, and perceived barriers. These concepts were proposed as accounting for people's "readiness to act." Other aspects of the model such as "cues to action," and efficacy, were added later to the model. Cues to action would activate readiness and stimulate overt behavior. In the KAP model, it is postulated that increased knowledge spurs people into changing their attitudes and eventually their behaviors. How knowledge specifically leads to behavioral change is not well explained.

As shown in Table 2, respondents who discussed harmful effects of smoking cigarettes with their family members were 39% (OR = 0.61, 95%CI 0.52, 0.71) less likely to report smoking compared to those who did not discuss with their family members. Compared to respondents who had not seen antismoking media messages, those who had seen a few or too many messages were 25% (OR = 0.75, 95%CI 0.58, 0.96) and 32% (OR = 0.68, 95%CI 0.55, 0.84) less likely to report smoking, respectively. Respondents who had seen too many antismoking messages at social gatherings were 1.30 (95%CI 1.06, 1.60) times more likely to report smoking compared to those who had not seen the antismoking message at social gatherings. Meanwhile, respondents who were taught that smoking makes teeth yellow, causes wrinkles and smokers smell badly were 38% (OR = 0.62, 95%CI 0.52, 0.74) less likely to report smoking compared to those who were not taught. Compared to respondents who were not taught that most people of the respondent's age do not smoke, those who were taught were 19% (OR = 0.81, 95%CI 0.69, 0.95) less likely to report smoking. Finally, respondents who reported that religious organizations discouraged young people from smoking were 30% (OR = 0.70, 95%CI 0.60, 0.82) less likely to report smoking compared to those who did not report the same.

This study has a number of limitations. Firstly, data were collected through self-reports. To the extent that study participants misreported, either intentionally or inadvertently, our results may be biased. The study also only recruited students. Adolescents who were out of school were, therefore, not represented. Furthermore reported current cigarette smoking was not verified by appropriate biomarkers such as cotinine level or exhaled carbon monoxide [35‐37].