Statistical analysis
BLOOD
Systolic and diastolic blood pressure were presented by factors related to participants’ characteristics, including sex, age, level of education, occupation, raw salt consumption and smoking status using one-way ANOVA. We presented blood pressure data as mean, and 95% confidence interval (CI) by domain-specific physical activity levels, total physical activity levels measured by MET-min categorized as insufficient physical activity and moderate and high physical activity. Blood pressure also presented by sedentary behaviours. We performed the analyses using a generalised linear model (GLM) after adjustment for age, sex, level of education, socioeconomic status, occupation, smoking status and raw salt consumption status. Blood pressured was also presented by awareness of and attitudes towards physical activity using GLM and adjusting for the same covariates. Due to the small sample, we checked the distribution of data. Associations for the individual item was based on binary categories, recategorized from multiple categorical responses. For example, the item “Do you know physical activity is good for health?” had four categories: “not at all”, “a little”, “a lot”, and “enormous” which was recategorized into two categories such as “not at all or a little” and “a lot or enormous”. Rasch analysis was used to convert categorical responses of the awareness of health benefits and attitudes towards physical activity to an interval scale to create a combined score from all the items. The combined score ranged from zero to 100, categorized into tertile with scores 0–40, defined as negative attitudes towards participating or organizing physical activity, 41–60 defined as neutral attitude and 61–100 as the positive attitude. With reference to positive attitudes, the estimated differences in mean with 95% CI systolic and diastolic blood pressure were obtained using GLM. Statistical software SPSS (SPSS Inc, version 27) was used for the analysis. For Rasch analysis, RUMM (RUMM2030) [