ABSTRACT
Quantile regression can be applied to model skewed variables, especially, when the objective is to model the tails of a response variable with highly skewed distribution. The aim of this study is to apply quantile regression to analyze urine iodine data and related factors in a Tehranian population. Data was collected in a cross-sectional study, in which 639 subjects, aged 19 years and over, were enrolled through randomized cluster sampling in Tehran between 2008-9. Due to the high skewness of 24 hr urinary iodine concentrations [UIC24] and to evaluate its extreme points, two linear quantile regression models were fitted. In model I, UIC24 was regressed on iodine content of salt and daily salt intake. These variables were replaced by iodine intake in model II, both models were adjusted by age. Model coefficients were estimated using the linear programming method and simplex algorithm. Significancy of the variables were evaluated by the bootstrap method. The Akaike information criterion [AIC] was used to assess the fitting of the models. All analyses were performed using R software version 2.12.2. Model I showed an increase in coefficients of iodine content of salt, daily salt intake, but a decrease in age coefficient in the length of the urinary iodine concentration percentiles. Model II showed similar results, but better fit [smaller AIC] in percentiles lower than median. Compared to ordinary regression, quantile regression models showed better fit, and a more complete picture and are recommended for modeling all parts of UIC24
ABSTRACT
Normal saliva has a critical role in maintenance of oral and dental health. Saliva is the first biologic fluid to confront the inhaled cigarette smoke. Chemical compounds in cigarette may change the amount and activity of salivary proteins and enzymes. The aim of this study was to compare the total protein concentration and amylase activity in smoker and nonsmoker men before dental practice. In a case - control study, 30 smoker men with mean age of 36 years and 30 nonsmoker men with mean age of 34 years who referred to Babol dental school were studied. After completing the questionnaire and before performing any dental work salivary samples were obtained. Their salivary samples were stored in -20°C and after centrifuge of saliva specimens, a modified Biuret method was used for measurement of total protein concentration. Caraway starch - iodine method was used to determine a-amylase activity on supernatants. Data were analyzed with SPSS software and t-test. The mean salivary a-amylase activity in smokers [121.47 +/- 22.41 IU/lit] was lower than in nonsmokers [133.52 +/- 18.73 IU/lit], but total protein concentration in smokers [257.43 +/- 49.18 mg/dl] was higher than nonsmokers [193.24 +/- 31.75mg/dl]. Although the mean a-amylase activity and total protein concentration were different in saliva of smoking and nonsmoking groups, but the difference wasn't statistically significant which suggests that smoking can not significantly change salivary total protein and a-amylase activity in smokers in comparison with nonsmokers