Statistical analysis
HTN, diabetes, dyslipidemia
CVD, RECRUITMENT, HTN, DYSLIPIDEMIA, DIABETES
All employees who attended follow-up visits at 24 months and had complete primary outcome data and other variables were included in the analysis. Considering the clustering effect, a mixed effects model with the subcenters as random effect was performed to examine the intervention effect on incidence of HTN and other outcomes over time by additionally adjusting for age at recruitment (continuous), sex (male or female), marital status (married or unmarried), educational attainment (elementary or below, junior high school, college or above), employment status (manual labor workers, desk job workers, administrative workers, others), workplace-affiliated hospital (WAH, WWH), history of dyslipidemia (yes or no), history of diabetes (yes or no), history of CVD (yes or no), family history of HTN (yes or no), and pharmacological treatment (yes or no). The hierarchical statistical techniques were used to capture the heterogeneity of workplace intervention. To handle the missing data on outcome and other covariates, a multiple imputation method was employed for sensitivity analyses to robust the primary outcome analyses. Exploratory analysis was also conducted in predefined subgroups, including sex, age, marital status, educational attainment, employment status, and workplace-affiliated hospital. The results were reported as rate (%), mean, standard deviation (SD), and 95% confidence interval (CI) when appropriate. For continuous outcomes, intervention effect was defined as the difference between the 2 groups, calculated as intervention (values at 24 months minus values at baseline) minus control (values at 24 months minus values at baseline). For dichotomous outcomes, the incidence of HTN was reported by relative risk (RR) and 95% CIs compared with the control group, with the improvements of lifestyle factors by odds ratio (OR) and 95% CIs. All data analyses were conducted using R version 4.1.0. A 2-tailed 