Statistical analysis
hypertension
SECONDARY, HYPERTENSION
We analysed the data according to the intention-to-treat principle. Participants who completed the baseline survey were analysed according to their randomly assigned group. We compared the difference in 24 hour urinary sodium excretion, as well as the secondary outcomes, between the two groups by using linear mixed models with participants nested within family units and families nested within community/village units. We included groups (intervention and control), time (baseline and end of the trial), (time×group) interactions, and potential confounding variables, including age, sex, body mass index, province, and education level, in the model, with the (time×group) interaction term indicating different changes by the group from baseline to the end of the trial. We did post hoc subgroup analyses considering age, sex, education level, family income, and hypertension status. To test the robustness of the primary findings, we did two sensitivity analyses: analysing the results without adjustment for the potential confounding variables and adding possibly incomplete 24 hour urine collections to the samples for analysis.We used SAS version 9.4 for the analyses and calculated all P values as two sided. We determined statistical significance by a false discovery rate of less than 0.05.