METHODS: Cigarette and alcohol use was assessed in a large cross-sectional national sample aged 50 years and above from the Irish Longitudinal Study on Ageing (TILDA) (n = 6,576). The Brief Ageing Perceptions Questionnaire (BAPQ) assessed individual's views of their own ageing across five domains. Study hypothesis that stronger beliefs on each of the BAPQ domains would be related to drinking and smoking was examined using multinomial logit models (MNLM). Regression parameter estimates for all variables were estimated relative risk ratios (RRR).
RESULTS: More women were non-drinkers (30 % vs. 20 %) and men displayed significantly higher alcohol use patterns. One in five older Irish adults was a current smoker (16.8 % of women, 17 % of men), and smoking and harmful drinking were strongly associated (P
MATERIALS AND METHODS: We analysed internationally comparable representative household survey data from 33,482 respondents aged ≥ 15 years in Indonesia, Malaysia, Romania, Argentina and Nigeria for determinants of tobacco use within each country. Socio-demographic variables analysed included gender, age, residency, education, wealth index and awareness of smoking health consequences. Current tobacco use was defined as smoking or use of smokeless tobacco daily or occasionally.
RESULTS: The overall prevalence of tobacco use varied from 5.5% in Nigeria to 35.7% in Indonesia and was significantly higher among males than females in all five countries. Odds ratios for current tobacco use were significantly higher among males for all countries [with the greatest odds among Indonesian men (OR=67.4, 95% CI: 51.2-88.7)] and among urban dwellers in Romania. The odds of current tobacco use decreased as age increased for all countries except Nigeria where. The reverse was true for Argentina and Nigeria. Significant trends for decreasing tobacco use with increasing educational levels and wealth index were seen in Indonesia, Malaysia and Romania. Significant negative associations between current tobacco use and awareness of adverse health consequences of smoking were found in all countries except Argentina.
CONCLUSIONS: Males and the socially and economically disadvantaged populations are at the greatest risk of tobacco use. Tobacco control interventions maybe tailored to this segment of population and incorporate educational interventions to increase knowledge of adverse health consequences of smoking.
METHODS: A historical review of official reports, news articles, and gray literature was undertaken to identify tobacco industry tactics and strategies to hamper government efforts in implementing stronger pictorial health warning regulations in four Asian jurisdictions (Cambodia, Hong Kong, Malaysia, and the Philippines).
RESULTS: Nineteen countries/jurisdictions in the WHO Western Pacific region currently require pictorial health warnings on cigarette packs, including some of the world's largest, in line with the WHO Framework Convention on Tobacco Control Article 11 Guidelines. In the four jurisdictions examined, tobacco industry interference consisted of lobbying and misinformation of high-level government officers and policy-makers, distributing industry-friendly legislative drafts, taking government to court, challenging government timelines for law implementation, and mobilizing third parties. Strong political leadership and strategic advocacy enabled governments to successfully overcome this industry interference.
CONCLUSION: The tobacco industry uses similar tactics in different jurisdictions to derail, delay, and weaken the implementation of effective health warning policies. Identifying and learning from international experiences can help anticipate and defeat such challenges.
MATERIALS AND METHODS: A cross-sectional epidemiological survey was conducted to detect the true prevalence of active smoking pregnant patients and the accuracy of self-reporting, investigate the sociodemographic risk factors and test the knowledge of pregnant patients on adverse effects of smoking. This involved 972 antenatal patients of a maternity hospital where participants completed a sociodemographic data survey and answered a knowledge questionnaire. Urine cotinine testing was carried out after informed consent.
RESULTS: The prevalence of active smokers was 5.2% (n = 50) with 3% (n = 29) being light smokers and 2.2% (n = 21) being heavy smokers. This was significantly higher than self-reported active smoking status of 3.7% (n = 36; P = 0.02). The Malay race, being aged less than 20 years and not having tertiary level qualifications independently increased the likelihood of being an active smoker. Knowledge of the adverse effects of smoking was generally good with a mean total score of 8.18 out of 10 but there were differences amongst the non-smokers, passive smokers, light smokers and active smokers (P = 0.012).
CONCLUSION: While the prevalence of active smoking among pregnant women is low in Singapore compared to other countries, this study substantiated the unreliability of self-reporting of smoking status in the pregnant population which could complicate referral to smoking cessation programmes. The lower awareness of the harms of smoking during pregnancy among smokers highlights a potential area for improvement.
METHODS: We analysed sequential Global Adult Tobacco Survey (GATS) data done at least at five years interval in 10 countries namely India, Bangladesh, China, Mexico, Philippines, Russia, Turkey, Ukraine, Uruguay, and Vietnam. We estimated weighted prevalence rates of smoking behaviors namely current smoking (both daily and non-daily), prevalence of hardcore smoking (HCS) among current smokers (HCSs%) and entire surveyed population (HCSp%), quit ratios (QR), and the number of cigarettes smoked per day (CPD). We calculated absolute and relative (%) change in rates between two surveys in each country. Using aggregate data, we correlated relative change in current smoking prevalence with relative change in HCSs% and HCSp% as well as explored the relationship of MPOWER score with relative change in smoking behaviors using Spearman' rank correlation test.
RESULTS: Overall daily smoking has declined in all ten countries lead by a 23% decline in Russia. In India, Bangladesh, and Philippines HCSs% decreased as the smoking rate decreased while HCSs% increased in Turkey (66%), Vietnam (33%) and Ukraine (15%). In most countries, CPD ranged from 15 to 20 sticks except in Mexico (7.8), and India (10.4) where CPD declined by 18 and 22% respectively. MPOWER scores were moderately correlated with HCSs% in both sexes (r = 0.644, p = 0.044) and HCSp% (r = 0.632, p = 0.05) and among women only HCSs% (r = 0.804, p = 0.005) was significantly correlated with MPOWER score.
CONCLUSION: With declining smoking prevalence, HCS had also decreased and quit rates improved. Ecologically, a positive linear relationship between changes in smoking and HCS is a possible evidence against 'hardening'. Continued monitoring of the changes in quitting and hardcore smoking behaviours is required to plan cessation services.
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.