Figure 2.

Stratified analysis on associations between long-term ${\mathrm{PM}}_{2.5}$ exposure ($10{-\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ increments) and systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) at baseline. Effect estimates (coefficients) are derived from multivariable linear regression analysis, and bars cover 95% confidence intervals. Results were adjusted for age (not in age-stratified analysis), sex (not in sex-stratified analysis), education level (not in education level–stratified analysis), smoking status (not in smoking-stratified analysis), alcohol drinking, leisure-time physical activity, occupational exposure to dust or organic solvents in the workplace, season, body mass index (BMI; not in BMI-stratified analysis), hypertension (not in hypertension-stratified analysis), diabetes (not in diabetes-stratified analysis), hyperlipidemia, and self-reported cardiovascular disease, stroke, or cancer. The lines with hollow circles from left to right represent the participants who were $<65\mathrm{y}\text{old}$, were males, had a high education level, were nonsmokers, had no hypertension, had no diabetes, and had BMI $<25{\mathrm{kg}/\mathrm{m}}^2$, respectively. The lines with solid circles from left to right represent the participants who were $\ge 65\mathrm{y}\text{old}$, were females, had a low education level, were smokers, had hypertension, had diabetes, and had $\text{BMI}\ge 25{\mathrm{kg}/\mathrm{m}}^2$, respectively. p-Values for interaction terms between ${\mathrm{PM}}_{2.5}$ (continuous variable) and each potential modifier (dichotomous variable) are presented in the figure.