Pharmacy, Vol. 12, Pages 171: Cardiovascular Diseases and Metabolic Medications in the Lebanese Population: A Post Hoc Analysis from a Nationwide Cross-Sectional Study

Pharmacy, Vol. 12, Pages 171: Cardiovascular Diseases and Metabolic Medications in the Lebanese Population: A Post Hoc Analysis from a Nationwide Cross-Sectional Study

Pharmacy doi: 10.3390/pharmacy12060171

Authors: Rony M. Zeenny Rachel Abdo Chadia Haddad Aline Hajj Rouba Karen Zeidan Pascale Salameh Jean Ferrieres

Objective: This study assesses the association of metabolic drugs (specifically hypoglycemic and hypolipemic agents) with cardiovascular diseases (CVD) among the Lebanese population and patients’ subgroups. Methods: A nationwide cross-sectional retrospective study was carried out in Lebanon. The survey collected information on sociodemographic characteristics, lifestyles, comorbidities, and medication use. Logistic regression models were employed to analyze the data and determine associations between CVD and metabolic drugs. Stratification analyses were performed based on diabetes and dyslipidemia status. Results: The study found significant associations with CVD among the 2048 participants. Higher scores on the Lebanese Mediterranean Diet Score (LMDS; ORa = 1.06), hypertension (ORa = 1.71), diabetes (ORa = 1.75), dyslipidemia (ORa = 1.89), family history of CVD (ORa = 1.58), and smoking (previous: ORa = 1.63, current: ORa = 2.15) were linked to increased CVD odds. Higher income (intermediate: ORa = 0.64, high: ORa = 0.40) was inversely related to it. A subsequent model that included hypoglycemic and lipid-lowering medications yielded similar results. However, neither hypoglycemic nor lipid-lowering medications demonstrated a significant association with CVD risk. A third regression model was conducted by taking the classes of drugs as an independent variable. Also, the result revealed that all the classes of medication were not associated with the risk of CVD. Stratification by diabetes revealed LMDS and hypertension as risk factors in both groups. Among non-diabetic participants, dyslipidemia (ORa = 2.40), current smoking (ORa = 2.28), and higher income (intermediate: ORa = 0.57, high: ORa = 0.62) were linked to CVD. Among people with diabetes, a family history of CVD (ORa = 2.69) increased the CVD odds, while being an employer (ORa = 0.49) lowered it. Stratification by dyslipidemia showed consistent risk factors, and higher LMDS (ORa = 1.07), diabetes (ORa = 2.14), hypertension (ORa = 1.79), and previous smoking (ORa = 1.95) were linked to CVD without dyslipidemia. Being a female (ORa = 0.52) and having a lower income (ORa = 0.40) were associated with lower CVD odds in those with dyslipidemia. Subgroup analyses showed that medications were not significantly associated with CVD odds among patients with diabetes or hyperlipidemia. Conclusions: This study’s findings highlight the importance of addressing modifiable risk factors and socioeconomic factors to reduce the burden of CVD. Targeted interventions and longitudinal research are necessary to optimize preventive strategies and improve the management of CVD in individuals using hypoglycemic and hypolipemic agents in low- and medium-income countries.