Objective: To estimate changes in the prevalence of current tobacco use and socioeconomic inequalities among male and female participants from 22 sub-Saharan African countries from 2003 to 2019.
Design, Setting, and Participants: Secondary data analyses were conducted of sequential Demographic and Health Surveys in 22 sub-Saharan African countries including male and female participants aged 15 to 49 years. The baseline surveys (2003-2011) and the most recent surveys (2011-2019) were pooled.
Exposures: Household wealth index and highest educational level were the markers of inequality.
Main Outcomes and Measures: Sex-specific absolute and relative changes in age-standardized prevalence of current tobacco use in each country and absolute and relative measures of inequality using pooled data.
Results: The survey samples included 428 197 individuals (303 232 female participants [70.8%]; mean [SD] age, 28.6 [9.8] years) in the baseline surveys and 493 032 participants (348 490 female participants [70.7%]; mean [SD] age, 28.5 [9.4] years) in the most recent surveys. Both sexes were educated up to primary (35.7%) or secondary school (40.0%). The prevalence of current tobacco use among male participants ranged from 6.1% (95% CI, 5.2%-6.9%) in Ghana to 38.3% (95% CI, 35.8%-40.8%) in Lesotho in the baseline surveys and from 4.5% (95% CI, 3.7%-5.3%) in Ghana to 46.0% (95% CI, 43.2%-48.9%) in Lesotho during the most recent surveys. The decrease in prevalence ranged from 1.5% (Ghana) to 9.6% (Sierra Leone). The World Health Organization target of a 30% decrease in smoking was achieved among male participants in 8 countries: Rwanda, Nigeria, Ethiopia, Benin, Liberia, Tanzania, Burundi, and Cameroon. For female participants, the number of countries having a prevalence of smoking less than 1% increased from 9 in baseline surveys to 16 in the most recent surveys. The World Health Organization target of a 30% decrease in smoking was achieved among female participants in 15 countries: Cameroon, Namibia, Mozambique, Mali, Liberia, Nigeria, Burundi, Tanzania, Malawi, Kenya, Rwanda, Zimbabwe, Ethiopia, Burkina Faso, and Zambia. For both sexes, the prevalence of tobacco use and the decrease in prevalence of tobacco use were higher among less-educated individuals and individuals with low income. In both groups, the magnitude of inequalities consistently decreased, and its direction remained the same. Absolute inequalities were 3-fold higher among male participants, while relative inequalities were nearly 2-fold higher among female participants.
Conclusions and Relevance: Contrary to a projected increase, tobacco use decreased in most sub-Saharan African countries. Persisting socioeconomic inequalities warrant the stricter implementation of tobacco control measures to reach less-educated individuals and individuals with low income.
METHODS: We analysed Demographic and Health Survey data on tobacco use collected from large nationally representative samples of men and women in 54 LMICs. We estimated the weighted prevalence of any current tobacco use (including smokeless tobacco) in each country for 4 educational groups and 4 wealth groups. We calculated absolute and relative measures of inequality, that is, the slope index of inequality (SII) and relative index of inequality (RII), which take into account the distribution of prevalence across all education and wealth groups and account for population size. We also calculated the aggregate SII and RII for low-income (LIC), lower-middle-income (lMIC) and upper-middle-income (uMIC) countries as per World Bank classification.
FINDINGS: Male tobacco use was highest in Bangladesh (70.3%) and lowest in Sao Tome (7.4%), whereas female tobacco use was highest in Madagascar (21%) and lowest in Tajikistan (0.22%). Among men, educational inequalities varied widely between countries, but aggregate RII and SII showed an inverse trend by country wealth groups. RII was 3.61 (95% CI 2.83 to 4.61) in LICs, 1.99 (95% CI 1.66 to 2.38) in lMIC and 1.82 (95% CI 1.24 to 2.67) in uMIC. Wealth inequalities among men varied less between countries, but RII and SII showed an inverse pattern where RII was 2.43 (95% CI 2.05 to 2.88) in LICs, 1.84 (95% CI 1.54 to 2.21) in lMICs and 1.67 (95% CI 1.15 to 2.42) in uMICs. For educational inequalities among women, the RII varied much more than SII varied between the countries, and the aggregate RII was 14.49 (95% CI 8.87 to 23.68) in LICs, 3.05 (95% CI 1.44 to 6.47) in lMIC and 1.58 (95% CI 0.33 to 7.56) in uMIC. Wealth inequalities among women showed a pattern similar to that of men: the RII was 5.88 (95% CI 3.91 to 8.85) in LICs, 1.76 (95% CI 0.80 to 3.85) in lMIC and 0.39 (95% CI 0.09 to 1.64) in uMIC. In contrast to men, among women, the SII was pro-rich (higher smoking among the more advantaged) in 13 of the 52 countries (7 of 23 lMIC and 5 of 7 uMIC).
INTERPRETATION: Our results confirm that socioeconomic inequalities tobacco use exist in LMIC, varied widely between the countries and were much wider in the lowest income countries. These findings are important for better understanding and tackling of socioeconomic inequalities in health in LMIC.
OBJECTIVE: We aimed to measure leptin and calorie intake among different nicotine dependent groups.
DESIGN: Cross-sectional study.
SETTING: Research department in school of medical sciences.
PATIENTS AND METHODS: Subjects were selected by purposive (non-probability) sampling and categorized as having low, moderate and high nicotine dependency based on the Fagerstrom Test for Nicotine Dependence (FTND) score. Diet was recorded by interview. Anthropometry, blood pressure, body composition, lipid profile, and physical activity level were measured accordingly. Fasting serum leptin was measured using a commercial ELISA kit.
MAIN OUTCOME MEASURE(S): Nicotine dependency, 24-hour diet, clinical anthropometric and clinical measurements.
RESULTS: In 107 Malay male smokers leptin concentration was inversely correlated with nicotine dependence. However, body weight, smoking period, blood pressure, body composition, lipid profile and physical activity level were not significantly different among low, moderately and highly dependent smoking groups. Leptin concentration and total calorie intake were also not significantly different among these groups.
CONCLUSION: Leptin concentration was inversely correlated with nicotine dependence, but leptin concentration and total calorie intake status were not significantly different among our different nicotine dependency subjects.
LIMITATIONS: Purposive sampling for subject recruitment and inaccurate information in the self-administered questionnaire.
Objective: The aim of this study was to develop and assess an equivalent modified FTND scale that measures the nicotine dependency via EC.
Materials and Methods: The investigator developed the equivalent modified FTND scale that scores identical to the original scale, that is, 0-10. The developed scale piloted among 15 EC single users, that is, use only EC verified by carbon monoxide (CO) level of <8ppm. The assessment of the scale was done among 69 EC single users and observed for 1 year to determine their nicotine status.
Results: The modified scale revealed an acceptable Cronbach α value of 0.725. Further test-retest reliability of the scale showed a satisfactory Spearman's rank correlation coefficient value of 0.730 (P > 0.05). A 1-year observation showed that of 69 single users, 11 single users completely stopped nicotine intake, 24 remained as EC single users, 15 shifted to dual-use, and 19 relapsed to TCG. Surprisingly, the EC users who completely stopped nicotine intake after 1 year had a low average nicotine dependence value of 3 that was measured by the modified FTND scale at the baseline.
Conclusion: The modified FTND scale precisely identifies the physical dependence to nicotine via EC. Therefore, as per this study results the modified FTND scale can be applied in any EC-related studies to assess nicotine dependency via EC.
Methods: A TCTM for students of dentistry was developed using ADDIE framework as a guide. Content and construct validation of the module was done by six subject experts using Delphi technique for obtaining consensus. Pilot testing was done on 20 students of third year BDS. Pre- and post-intervention assessment of knowledge, attitude, self-confidence was done using learning outcomes questionnaire. Ability to correctly identify oral manifestations was assessed using extended item MCQs and tobacco counseling skills using a modified KEECC. The difference in mean scores were computed and subjected to further statistical analysis using SPSS version 22.
Results: There was a significant improvement in post intervention scores for mean knowledge (5.5 ± 1.4 to 13.2 ± 1.1), attitude (5.6 ± 0.9 and 8.5 ± 0.5), self-confidence (1.5 ± 0.5 and 3.1 ± 0.2), ability to correctly identify oral manifestations (5.2 ± 1.4 and 9.4 ± 0.8) and tobacco counseling skills.
Conclusion: It is possible to introduce the module in the existing curriculum and its effectiveness evaluation shows benefit in terms of Kirkpatrick's Level 1, 2, 3 (improvement in knowledge, attitude, self-confidence, ability to identify oral manifestations, and tobacco counseling skills) of training effectiveness.