Fig. 3: Lifestyle factors across three populations.
a Longitudinal changes in macronutrient trends nationally from 1998 to inception of HELIOS study in 2022 (n = 10,004). Ethnic variations in b macronutrients (proportion to total energy intake, n = 8119), c diet quality represented by a modified DASH score (range from 0 for low quality to 35 for high quality, data points represent mean DASH score; error bars represent standard errors, n = 8119) and d top 20 FFQ foods (servings/day) significantly different across ethnicities within HELIOS study. e Physical activity (data points represent mean total MET-minutes per week; error bars represent standard errors, n = 8119) and f Accelerometer-based physical activity according to the levels of self-reported physical activity (R = 0.23, two-sided p = 1.7 × 10-11 from Kruskal-Wallis rank sum test). g The proportion of people who meet the WHO guideline of physical activity by ethnicity and the proportion of physical activity across different domains (n = 7853). h The relationships between lifestyle factors and cardiometabolic phenotypes are heterogeneous across ethnic groups. Data points represent the coefficients derived from linear regression model; error bars represent 95% confidence intervals, n = 7307. The associations of DASH with DBP were similar to those with SBP, the effect size were: β(SE)DASH->SBP = −0.04 (0.03) in Indian group, compared to −0.02 (0.01) and −0.01 (0.03) in Chinese and Malay groups). DASH dietary approaches to stop hypertension, IPAQ International Physical Activity Questionnaire, MET metabolic equivalent of task, MUFA monounsaturated fat, PUFA polyunsaturated fat, SE standard error, SFA saturated fat, WHO World Health Organization.
