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.
METHODS: We analyzed school-based Global Youth Tobacco Survey (2014-2019) microdata from 18 WPR countries and estimated weighted prevalence rates of ST consumption, cigarette smoking, and dual use. We used multilevel binary logistic regression to examine the associations of ST consumption and dual use with demographic variables, exposure to pro-tobacco and anti-tobacco factors, national income, and MPOWER indicators.
RESULTS: Data from 58,263 school-going youth were analyzed. The prevalence of past 30-day ST consumption was highest in Kiribati (42.1%), the Marshall Islands (26.1%), Micronesia (21.3%), Palau (16.0%), and Papua New Guinea (15.2%). In adjusted multilevel models, ST consumption and dual use were significantly associated with sex, age, parental smoking, pro-tobacco factors, national income, and MPOWER score. For each unit increase in score for cessation programs, we observed approximately 1.4-fold increases in the odds of youth ST consumption (adjusted odds ratio [aOR], 1.38; 95% confidence interval [CI], 1.15 to 1.66) and dual use (aOR, 1.47; 95% CI, 1.16 to 1.86). Similarly, for each unit increase in score for health-related warnings, the odds of both ST consumption (aOR, 0.47; 95% CI, 0.42 to 0.53) and dual use (aOR, 0.35; 95% CI, 0.30 to 0.42) decreased by approximately 60%.
CONCLUSIONS: The prevalence of youth ST consumption was substantial in the Pacific Islands, exceeding that of cigarette smoking in some countries. Implementing MPOWER measures for ST products could help reduce ST consumption.
AIMS AND METHODS: Global Youth Tobacco Survey (GYTS)s from Georgia, Iraq, Italy, Latvia, Montenegro, Paraguay, Peru, Qatar, Romania, and San Marino were analyzed. Changes in prevalence of "awareness of e-cigarettes," "ever use" (even tried a few puffs) and "current use" (during last 30 days) of e-cigarettes and cigarette smoking, and "dual use" (both e-cigarette and cigarette smoking) between baseline (2013 and 2014) and most recent (2017-2019) surveys were estimated.
RESULTS: "Awareness of e-cigarettes" and "ever e-cigarette use" significantly increased (p 50% in most countries. During the most recent surveys, "current e-cigarette" use was > 10% in five countries Italy (18.3%) and Latvia (18.5%) being the highest. Cigarette smoking significantly declined in Italy, Latvia, Peru, and San Marino (p tobacco use among youths and comprehensive tobacco control policies inclusive of e-cigarettes are needed.
IMPLICATIONS: Secondary data analyses of serial GYTSs in 10 countries showed that both awareness of e-cigarette and e-cigarette use has increased among school-going youth aged 13-15 years. A concurrent increase in "dual use" of e-cigarettes and cigarette smoking during the last 30 days in all 10 countries indicates continued cigarette smoking in the absence of e-cigarettes because of the common risk construct of tobacco product use. Results call for continued surveillance of both e-cigarettes and cigarette smoking among school-going youth. Comprehensive tobacco control measures inclusive of e-cigarettes should be implemented to reduce tobacco use among the youth.
Methods: This comparative cross-sectional study was conducted among healthy women. The cases included those women exposed to SHS, and the controls included those women not exposed to SHS. SHS exposure was defined as being exposed to SHS for at least 15 min for 2 days per week. Venous blood was taken to measure the metabolic markers (high molecular weight adiponectin, insulin level, insulin resistance, and nonesterified fatty acids), oxidative stress markers (oxidized low density lipoprotein cholesterol and 8-isoprostane), and inflammatory markers (high-sensitivity C-reactive protein and interleukin-6). A hair nicotine analysis was also performed. An analysis of covariance and a simple linear regression analysis were conducted.
Results: There were 101 women in the SHS exposure group and 91 women in the non-SHS exposure group. The mean (with standard deviation) of the hair nicotine levels was significantly higher in the SHS exposure group when compared to the non-SHS exposure group [0.22 (0.62) vs. 0.04 (0.11) ng/mg; P = 0.009]. No significant differences were observed in the high molecular weight adiponectin, insulin and insulin resistance, nonesterified fatty acids, 8-isoprostane, oxidized low density lipoprotein cholesterol, interleukin-6, and high-sensitivity C-reactive protein between the two groups. The serum high molecular weight adiponectin was negatively associated with the insulin level and insulin resistance in the women exposed to SHS. However, no significant relationships were seen between the high molecular weight adiponectin and nonesterified fatty acids, 8-isoprostane, oxidized low density lipoprotein cholesterol, high-sensitivity C-reactive protein in the SHS group.
Discussion: There were no significant differences in the metabolic, oxidative stress, and inflammatory markers between the SHS exposure and non-SHS exposure healthy women. A low serum level of high molecular weight adiponectin was associated with an increased insulin level and resistance in the women exposed to SHS.
METHODS: This scoping review intended to investigate published studies on the current prevalence and incidence of oral cancer in LMICs. The review was conducted applying the search words "Oral Cancer" and "Mouth neoplasm" as the Medical Subject Heading (MeSH) major topic and "Epidemiology" and ("prevalence" OR "incidence") as the MeSH subheading; the search was supplemented by cross-references. Included studies met the following criteria: original studies, reporting of prevalence or incidence rates, population-based studies, studies in English language and studies involving humans.
RESULTS: The sample sizes ranged from 486 to 101,761 with 213,572 persons included. Buccal mucosa is one of the most common sites of oral cancer, associated with the widespread exposure to chewing tobacco. The incidence is likely to rise in the region where gutkha, pan masala, pan-tobacco and various other forms of chewing tobacco are popular.
CONCLUSION: This review contributes to useful information on prevalence and incidence estimates of oral cancer in LMICs.