Introduction: Recommendations for self-regulatory lifestyle behaviors - SRLB, such as reducing salt, or calories, often focus on reading nutrition labels. While these are correlated with cardiovascular outcomes, their causal effects are underexplored. Hypothesis: As covariance-based structural equation modeling - SEM, examines multivariate causal relationships in one model while considering measurement error, we propose using SEM to hypothesize that label reading and SRLB will improve cardiovascular outcomes (Figure1a) Methods: SEM was applied to National Health and Nutrition Examination Study 2017 - 2018 data in adults over 18 years of age, adjusted for education, age, gender, and ethnicity. Label reading included the use of calorie and sugar information. SRLB included weight loss, increasing exercise, and reducing salt and fat. Results: Of 4260 adults, 51.9% were female, with a mean age of 51.46 ± 17.5 (Table 1b). Extensive effects of SRLB, on HDL-C (β= .12, p <.01), Total Cholesterol - TC (β= -.17, p <.001); and label reading, on Blood Pressure - BP (β = -.73, p <.001), Triglycerides - TG (β = -.49, p <.001) were noted. BMI (β = -.10, p <.01) and Hba1c (β = -.13, P<.001) improved with SRLB, but label reading showed no effect. Higher education increased BP (β =.1, P<.001), but decreased Hba1c (β = -.07, P<.001) and ethnicity had a negative effect on BMI (β = -.1, P<.001) (Table 1c). Conclusions: Using SEM, we demonstrate the causal effects of dietary and lifestyle behaviors on cardiovascular outcomes. The extensive impact of label reading illustrates its efficacy in managing hypertension and dyslipidemia, but the absence of effect on weight and blood sugar management, and the varied effect of education, and ethnicity, need to be explored. In addition, our findings may underscore the need for culturally tailored lifestyle recommendations that achieve caloric balance by interpreting calorie and sugar information in the context of serving size and caloric expenditure.