Proc surveyreg

I intake can vary between population groups. The observed I intake from natural sources
(excluding iodised salt and supplements) was estimated for several population
characteristics (age, sex, BMI, income of the head of the household, education (for
children, highest education of parents), season, region) using Proc SurveyMeans (SAS 9.2).
With linear regression (Proc SurveyReg (SAS 9.2); P<0·05
statistically significant) it was studied how the intake of I naturally present in foods
and population characteristics were associated, similar to Huybrechts et al.⁽²⁶⁾. These analyses were performed separately for children (7–18 years) and
adults (19–69 years). The variables I intake and I intake/418 kJ (100 kcal) were natural
log transformed to improve normality of the data and residuals. Potential outliers were
detected and analyses were performed including and excluding these outliers to study the
impact on the results. Linear regression was also performed to study the association
between the intake of two food groups (milk and cheese) contributing most to the intake of
I naturally present in foods (excluding iodised salt and supplements) and to the intake of
bread (a main source of iodised salt), among consumers only. These intake variables were
square root transformed to improve normality of the data and residuals, except for cheese
intake among adults that was transformed with a natural log.

The baseline study characteristics are presented as mean (SE) for continuous variables and as the percentage (SE) for categorical variables. A linear regression model using “PROC SURVEYREG” in SAS 9.2 (SAS Institute Inc., Cary, NC) was used to test for linear trends over time and the Rao-Scott chi-square test using “PROC SURVEYFREQ” in SAS 9.2 (SAS Institute Inc., Cary, NC) were used. We calculated the age-standardized prevalence and the 95% confidence intervals (CIs) for chronic lymphocytic thyroiditis by gender and year using direct standardization with the world standard population (using “PROC SURVEYREG” in SAS 9.2). We also used binomial regression with a log link to calculate the age-adjusted prevalence ratios and 95% CIs for chronic lymphocytic thyroiditis by gender [24] (link). Additionally, we considered years as a continuous variable when testing for linear trends in the age-adjusted prevalence ratio of chronic lymphocytic thyroiditis by sex. A p<0.05 was considered statistically significant.