We had three AOBP measurements obtained on Day 1 (for all participants) and three additional follow-up AOBP measurements obtained after about 1 month from those with high BP on Day 1. We estimated the prevalence of high BP and their corresponding 95% confidence intervals, at each step in the screening process, using interval estimate for binomial proportion. The first step, used the first AOBP measurement (in a series of three) obtained on Day 1 to screen for high BP using the ‘screening algorithm’ of the 2017 American standard guideline18. Participants with BP ≥ 120/80 mmHg if aged ≥ 13 years or BP ≥ 90th percentile if aged < 13 years were regarded as having high BP. The second step used the average of the second and third AOBP measurements (in a series of three) obtained on Day 1 to screen for participants with high BP using the BP percentile tables. The third step only involved participants with high average AOBP on day 1. We used average of second and third follow-up AOBP measurements (in a series of three) obtained on Day 2 to obtain their ‘final’ BP using the BP percentile tables18. Participants whose systolic and/or diastolic BP ≥ 90th percentiles for their age, sex and height were regarded as having sustained high BP and underwent 24-h ABPM. We then categorized 24-h average BP as either normal BP OR pre-hypertension OR hypertension OR severe hypertension, depending on ABPM 95th percentile score and/or systolic or diastolic BP load ≥ 25% as recommended by the 2014 American Heart Association guideline20. Participants whose average 24-h BP was categorized as pre-hypertension, hypertension or severe hypertension were regarded as having confirmed high BP while those with normal BP using 24-h ABPM were regarded as having white coat hypertension.

Participants’ demographic, biological and behavioral characteristics were separately summarized for males and females using median [IQR] for continuous variables and proportions for categorical variables. To test for statistical significant differences between males and females, Student’s T-test (continuous variable) and Chi-squared test (for categorical variable) were used.

To assess for factors associated with sustained high BP, we compared socio-demographic, behavior and biological characteristics of participants with sustained high BP to those with normal AOBP measurements. Student’s T test (continuous variable) and Chi-squared test (categorical variable) were used to test for statistical significant differences between the groups. Logistic regression analyses adjusted for age and sex (priori confounders) were conducted on characteristics with statistical significance (p ≤ 0.05) during initial analyses.

Student’s T test (continuous variables) and (Fisher’s exact test) were used to assess for significant differences in ABPM characteristics between males and females. In order to adjust for potential type 1 error resulting from multiple comparisons, we only reported ABPM characteristics with p-value < 0.01 as statistically significant. Statistical analysis was performed using STATA IC version 14 (StataCorp, College Station, Texas, USA).

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