BACKGROUND: Considering the general trend toward an increased occurrence of cardiovascular and mental health diseases, we studied the relationship between the presence of trait and state anxiety and the alteration of serum cortisol, lipid, and glycemia levels. MATERIAL AND METHODS: The study assessed 90 full-time workers waist circumferences, as well as their cortisol levels at 8 AM and 4 PM, and their fasting serum glucose and lipid profiles. The construct of trait and state anxiety was assessed by means of the Inventory of Trait-State Anxiety (IDARE Spanish version). RESULTS: The state anxiety scale showed high reliability (ω = 0.94, α = 0.939). Moderate to high state anxiety was observed in 61.1% of participants, while 71.1% had moderate to high trait anxiety. Most participants (94.4%) had AM and PM cortisol levels within normal ranges. PM cortisol levels were lower than AM cortisol levels in 95.6% of participants (86/90). Dyslipidemia was present in 60.4% of participants. No significant sex differences were found in AM and PM cortisol or anxiety levels, except for triglycerides, which were higher in men (p = 0.013). State anxiety was positively correlated with PM cortisol levels (r = 0.232, p = 0.028), no significant associations were found with AM cortisol or age. A significant association was observed between waist circumference and fasting glycemia, with 68.9% of participants exceeding the recommended waist circumference threshold. Obesity was significantly associated with hyperglycemia (p = 0.010). An ANOVA revealed a significant effect of state anxiety on evening cortisol levels (F(2, 87) = 7.336, p = 0.001), with the high state anxiety group exhibiting the highest PM cortisol levels. Additionally, a t-test found a significant difference in triglyceride levels between the presence and absence of state anxiety t (87.999) = -2.244, p = 0.027. CONCLUSIONS: The presence of state anxiety proved to be the type of anxiety most associated with increased evening cortisol levels and triglyceride levels. Understanding the relationships between mental states and biochemical physical conditions will be essential in the future for maximizing the benefits of technological developments applied to the diagnosis, prognosis, and monitoring of patients' overall health.