MATERIALS AND METHODS: A total of 81 cases of oral cancers were matched with 162 controls in this hospital-based study. Information on sociodemographic characteristics and details of risk habits (duration, frequency and type of tobacco consumption and betel quid chewing) were collected. Association between smoking and betel quid chewing with oral cancer were analysed using conditional logistic regression.
RESULTS: Slightly more than half of the cases (55.6%) were smokers where 88.9% of them smoked kretek. After adjusting for confounders, smokers have two fold increased risk, while the risk for kretek consumers and those smoking for more than 10 years was increased to almost three-fold. Prevalence of betel quid chewing among cases and controls was low (7.4% and 1.9% respectively). Chewing of at least one quid per day, and quid combination of betel leaf, areca nut, lime and tobacco conferred a 5-6 fold increased risk.
CONCLUSIONS: Smoking is positively associated with oral cancer risk. A similar direct association was also seen among betel quid chewers.
OBJECTIVE: This study aimed to determine the awareness and knowledge of the signs, symptoms and risk factors of oral cancer among a Siamese ethnic group in Tumpat, Kelantan.
METHODS: A cross-sectional study was conducted, using a guided questionnaire on sociodemography, habits, awareness and knowledge of the signs, symptoms and risk factors of oral cancer. Individuals under 18 years old and who had been diagnosed with oral cancer were excluded from this study.
RESULTS: A total of 195 respondents participated, 61.5% were female and the mean age was 46 (1.64). About 41% of the respondents had received secondary education and 35.4% were illiterate. Most respondents were self-employed (21.5%), followed by farmers (19.5%) and housewives (20%). The majority of them had a monthly income that fell below the poverty level of RM 830 (76.9%). Among the respondents, 22.6% had the habit of smoking, 25.6% consumed alcohol, 8.2% were betel quid chewers and 2.6% chewed tobacco. Out of 195 respondents, only 6.7% were aware of oral cancer. About 16.9% of the respondents correctly answered all of the questions regarding the signs and symptoms of oral cancer and only 4.1% knew the risk factors of oral cancer.
CONCLUSION: The awareness and knowledge of oral cancer in this targeted population were unsatisfactory. Future effective health promotion programs and education should be emphasised.
MATERIALS AND METHODS: A total of 60 subjects were selected for this study. 40 subjects presented with periodontitis, which included 20 snuff users (SP) and 20 nonsnuff users (NS). 20 periodontally healthy patients formed the controls (healthy control: HC). The clinical parameters recorded were gingival index (GI), plaque index, calculus index, bleeding on probing (BOP), probing depth (PD), recession (RC), and clinical attachment level (CAL). The IL-1 β and IL-8 levels were assessed through enzyme-linked immunosorbent assay (Quantikine(®)). Analysis of variance (ANOVA), post-hoc Tukey's, Kruskal-Walli's ANOVA and Mann-Whitney test was used for comparison among groups and P > 0.05 was considered statistically significant.
RESULTS: No significant difference was seen in levels of IL-1 β and IL-8 between SP and NS groups (P = 0.16, 0.97). However, both the periodontitis groups (SP and NS) had increased IL-β levels when compared to HC group (P = 0.01, 0.001). The snuff users showed significant increase in GI, BOP, RC, and CAL when compared with NS (P = 0.002, 0.001, 0.012, 0.002) whereas NS group had significant increase in PD (P = 0.003).
CONCLUSION: Within the limitations of this study, use of snuff does not affect the host inflammatory response associated with periodontitis and leads to RC and increased CAL due to local irritant effect.
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.
Methods: A link to the online survey was sent to healthcare professionals (HCPs) in Asia interested in AYA cancer care. Questions covered the demographics and training of HCPs, their understanding of AYA definition, availability and access to specialised AYA services, the support and advice offered during and after treatment, and factors of treatment non-compliance.
Results: We received 268 responses from 22 Asian countries. There was a striking variation in the definition of AYA (median lower age 15 years, median higher age 29 years). The majority of the respondents (78%) did not have access to specialised cancer services and 73% were not aware of any research initiatives for AYA. Over two-thirds (69%) had the option to refer their patients for psychological and/or nutritional support and most advised their patients on a healthy lifestyle. Even so, 46% did not ask about smokeless tobacco habits and only half referred smokers to a smoking cessation service. Furthermore, 29% did not promote human papillomavirus vaccination for girls and 17% did not promote hepatitis B virus vaccination for high-risk individuals. In terms of funding, 69% reported governmental insurance coverage, although 65% reported that patients self-paid, at least partially. Almost half (47%) reported treatment non-compliance or abandonment as an issue, attributed to financial and family problems (72%), loss of follow-up (74%) and seeking of alternative treatments (77%).
Conclusions: Lack of access to and suboptimal delivery of AYA-specialised cancer care services across Asia pose major challenges and require specific interventions.
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.
METHODS: Oral swab samples were collected from smokers, smokeless tobacco users, and healthy controls (n = 44). Microbial DNA was extracted and the 16S rRNA gene profiled using the Illumina MiSeq platform. Sequencing reads were processed using DADA2, and taxonomical classification was performed using the phylogenetic placement method. Differentially abundant taxa were identified using DESeq2, while functional metagenomes based on KEGG orthology abundance were inferred using LIMMA.
RESULTS: A significantly higher microbial diversity was observed in smokeless tobacco users and smokers relative to controls (P smokeless tobacco users. Levels of Fusobacterium spp., Saccharibacterium spp., and members of Shuttleworthia were elevated in smokers when compared to controls (BH adj P smokeless tobacco users relative to controls (BH adj P smokeless tobacco users relative to both controls, and smokers were similar and involved amino acid metabolism including glutamate and aspartate biosynthesis and degradation (log FC > 1.5; BH adj P smokeless tobacco users as compared to healthy controls implicates a significant role of microbes and their metabolites in diseases associated with tobacco use including oral cancer.
CLINICAL RELEVANCE: Future efforts in preventive, diagnostic, curative, and prognostic strategies for diseases associated with tobacco use in smokers and smokeless tobacco users could incorporate the oral microbiome.
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.