Concomitant medications
Usage of medications during study period will be recorded.
5. Populations and subgroups to be analysed
5.1 Populations
Intention-to-treat (ITT)
All randomised study subjects. This will be seen as the primary population for the analysis.
Per Protocol (PP)
All randomised study subjects completing the whole study period (complete cases). For a specific
analysis, study subjects with missing data on any of the variables in the model will be excluded from
the analysis. Analyses of this population is seen as a sensitivity analysis to investigate whether
conclusions are sensitive to assumptions regarding the pattern of missing data.
5.2 Subgroups
Six subgroups will be analysed. All subgroups will be analysed using both ITT and PP populations.
High-high
All randomised study subjects having copeptin concentration above the previously specified cut-off
values, 6.1 pmol/L (women) or 10.7 pmol/L (men), at both population screening and baseline visit.
Top tertile
All randomised study subjects having copeption concentration in the top tertile (gender specific) at
baseline visit.
Diabetes mellitus
All randomised study subjects will be divided into two subgroups according to having diabetes
mellitus or not at baseline visit.
Gender
All randomised study subjects will be divided into two subgroups according to gender.
6. Analyses
All outcomes will be presented using descriptive statistics; normally distributed data by the mean and
standard deviation (SD) and skewed distributions by the median and interquartile range (IQR). Binary
and categorical variables will be presented using counts and percentages. SAS 9.4 will be used for all
statistical analysis.
The subsections below will describe analyses in addition to the descriptive statistics.
6.1 Primary outcome
The primary analysis will compare intervention groups (water supplementation vs control treatment) on
their mean change in fasting plasma glucose between baseline and 12 months using a linear mixed
model. Difference in fasting plasma glucose from baseline to time points where it is measured during
the study (6 and 12 months) will be the dependent variable. Study subjects will be considered as random
effects, treatment group and visit number as fixed effects. Baseline value of fasting plasma glucose will
be included as a covariate. The estimated difference in mean change from baseline to 12 months and the
corresponding 95 % confidence interval (CI) will be presented.
6.2 Secondary outcomes
Cardiometabolic risk factors will be analysed using the same method as for the primary outcome,
including usage of the baseline value for the actual factor as a covariate. Diabetes incidence will be
analysed using logistic regression, the odds ratio (OR) including 95 % CI will be presented.