Nicotine replacement therapy use among adolescent smokers seeking cessation treatment.

OBJECTIVE: To examine the correlates of prior nicotine replacement therapy (NRT) in an urban sample of adolescent smokers seeking smoking cessation treatment. DESIGN: Adolescents were recruited via radio, TV and print advertisements for participation in treatment studies. Participants completed a structured interview usinga prescreeningquestionnaire. SETTING: Data were collected via a telephone interview by trained research personnel. PARTICIPANTS: A sample (N=1879) cessation treatment-seeking volunteer boys (38.2%) and girls (61.8%) aged 12 to 17 years, from a diverse ethnic background residing in the Baltimore, Maryland metropolitan area. INTERVENTIONS: No interventions were used in this observational study. MAIN OUTCOME MEASURES: Use of NRT in adolescents stratified by age, Fagerstrom Test of Nicotine Dependence (FTND), and race/ethnicity. RESULTS: The sample had a mean FTND score of 5.7 (SD = 2.2). About 41% smoked 11 to 20 cigarettes per day. Adolescent smokers who had used NRT were statistically but only marginally older than those who had not (15.9 vs 15.7 years; t-test= -2.60, P=0.01). FTND score, a measure of nicotine dependence, was higher among those who had used NRT (6.0 vs 5.6; t-test= -3.37, P= .001). African American adolescents were less likely to have used NRT than their European American counterparts (33.0% vs 61.2%; chi2=16.09, P<.003). After stepwise logistic regression analyses, age, FTND and race/ethnicity remained predictors of NRT use. CONCLUSION: Our results show differences in NRT use patterns based on age, FTND, and race/ethnicity. European American youths are more likely than their 'other' counterparts to use NRT, after adjusting for age and smoking severity, whereas, African American youth are less likely than their 'other' counterparts to use NRT. These findings suggest racial/ethnic disparities in accessing smoking cessation modalities among adolescents. Further research is needed to fully elucidate factors contributing to these differences in order to facilitate increased smoking cessation rates among all adolescents

Level of oral health impacts among patients participating in PEARL:a dental practice-based research network

OBJECTIVES: To determine whether participants of a dental practice-based research network (PBRN) differ in their level of oral health impact as measured by the Oral Health Impact Profile (OHIP) questionnaire. METHODS: A total of 2410 patients contributed 2432 OHIP measurements (median age = 43 years; interquartile range = 28) were enrolled in four dental studies. All participants completed the Oral Health Impact Profile (OHIP-14) during a baseline visit. The main outcome of the current study was the level of oral health impact, defined as follows: no impact (“Never” reported on all items); low (“Occasionally” or “Hardly ever” as the greatest frequency score reported on any item); and high (“Fairly often” or “Very often” as the greatest frequency reported on any item). Polychotomous logistic regression was used to develop a predictive model for the level of oral health impact considering the following predictors: patient’s age, gender, race, practice location, type of dentist, and number of years the enrolling dentist has been practicing. RESULTS: A high level of oral health impacts was reported in 8% of the sample; almost a third (29%) of the sample reported a low level of impacts, and 63% had no oral health impacts. The prevalence of impacts differed significantly across protocols (P<0.001). Females were more likely to be in the high oral impact group than the no impact group compared to males (OR=1.46; 95% CI= 1.06–1.99). African-Americans were more likely to report high oral impacts when compared to other racial/ethnic groups (OR=2.11; 95% CI = 1.26–3.55). Protective effects for being in the high or in the low impact groups were observed among patients enrolled by a solo practice (P<0.001) or by more experienced dentists (P=0.01). A small but highly significant statistical association was obtained for patient age (P<0.001). In the multivariate model, patient’s age, practice size and gender were found to jointly be significant predictors of oral health impact level. CONCLUSIONS: Patients’ subjective report of oral health impact in the clinical setting is of importance for their health. In the context of a dental PBRN, the report of oral health-related quality of life (OHRQoL) was different across four dental studies. The observed findings validate the differential impact that oral health has on the patients’ perception of OHRQoL particularly among specific groups. Similar investigations to elucidate the factors associated with patient’s report of quality of life are warranted