Determinants of Salivary Cotinine among Smokeless Tobacco Users : A Cross-Sectional Survey in Bangladesh

INTRODUCTION: More than 80% of all smokeless tobacco (ST) products in the world are consumed in South Asia; yet little is known about their consumption behaviour, addictiveness, and toxic properties. This paper, for the first time, describes associations between salivary cotinine concentrations among ST users in Bangladesh and their socio-demographic characteristics and tobacco use behaviours. METHODS: In a survey of ST users in Dhaka, Bangladesh, we purposively recruited 200 adults who were non-smokers but consumed ST on a regular basis. In-person interviews were conducted to obtain information about socio-demographic and ST use behaviours, and saliva samples were collected to measure cotinine concentration. Simple and multiple linear regression analyses were conducted to test associations between the log transformed salivary cotinine concentration and other study variables. RESULTS: The geometric mean of cotinine concentration among ST users was 380ng/ml (GSD:2). Total duration of daily ST use in months had a statistically significant association with cotinine concentration. Other ST use characteristics including type and quantity of ST use, swallowing of tobacco juice, urges and strength of urges and attempts to cut down on tobacco use were not found to be associated with cotinine concentration in a multivariable model. CONCLUSION: This is the first report from Bangladesh studying cotinine concentration among ST users and it points towards high levels of addiction. This warrants effective tobacco control policies to help ST cessation and prevention

Risk-adjustment of diabetes health outcomes improves the accuracy of performance benchmarking

Benchmarking clinical performance by comparing diabetes health outcomes across healthcare providers drives quality improvement. Non-care related patient risk factors are likely to confound clinical performance, but few studies have tested this. This cross-sectional study is the first Australian investigation to analyse the effect of risk-adjustment for non-care related patient factors on benchmarking. Data from 4,670 patients with type 2 (n = 3,496) or type 1 (n = 1,174) were analysed across 49 diabetes centres. Diabetes health outcomes (HbA1c levels, LDL-cholesterol levels, systolic blood pressure and rates of severe hypoglycaemia) were risk-adjusted for non-care related patient factors using multivariate stepwise linear and logistic regression models. Unadjusted and risk-adjusted funnel plots were constructed for each outcome to identify low-performing and high-performing outliers. Unadjusted funnel plots identified 27 low-performing outliers and 15 high-performing outliers across all diabetes health outcomes. After risk-adjustment, 22 (81%) low-performing outliers and 13 (87%) high-performing outliers became inliers. Additionally, one inlier became a low-performing outlier. Risk-adjustment of diabetes health outcomes significantly reduced false positives and false negatives for outlier performance, hence providing more accurate information to guide quality improvement activity