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Smoking is a well-documented risk factor of cardiovascular diseases (CVD) and premature death. Previous studies have focused on smoking duration and total cigarette consumption, but a 2024 paper by Li et al. highlights the time between waking up and smoking the first cigarette as a risk factor of mortality, noting that smoking ≤5 minutes after waking is strongly linked to a higher risk of mortality and a higher chance of incident myocardial infarction or stroke, and may be a sign of nicotine dependence. Another study by Hu et al. (2024) states that early-morning smoking more strongly correlates with incident type 2 diabetes than total cigarette consumption, adding to preceding evidence that early-morning smoking is linked to type 2 diabetes and chronic obstructive pulmonary disease (COPD). The demonstrated association with adverse health outcomes and early-morning smoking suggests delayed time to first cigarette can be a useful target as part of smoking interventions. These findings indicate the necessity of public health policies targeting smoking behaviour in addition to cessation as a way to decrease the associated disease burden.

(1) <b>Background</b>: Psychological flexibility, the ability to adapt to changing demands while staying true to personal values, is linked to better health behaviors. However, its relationship with cardiovascular health behaviors, particularly in Filipino populations, remains underexplored. (2) <b>Aim</b>: This study aimed to examine the relationship between psychological flexibility and cardiovascular health behaviors among outpatients in Rizal, Philippines, focusing on BMI, smoking, physical activity, and dietary habits. (3) <b>Methods</b>: A cross-sectional, descriptive-correlational design was used with 100 outpatient participants from selected hospitals. Psychological flexibility was measured using the Acceptance and Action Questionnaire-II (AAQ-II), and cardiovascular health behaviors were assessed using a modified version of the American Heart Association’s Life Simple 7 tool. Descriptive statistics and Pearson’s correlation were applied. (4) <b>Results</b>: The findings showed that respondents had neutral levels of psychological flexibility. While most exhibited intermediate BMI and physical activity, dietary habits varied. A significant positive correlation was found between psychological flexibility and whole grain consumption. However, no significant associations were found with BMI, smoking, or physical activity. (5) <b>Conclusions</b>: Psychological flexibility appears to influence specific health behaviors, such as dietary choices, but does not strongly correlate with other cardiovascular health behaviors. Further research is needed to explore its broader role in cardiovascular disease prevention.

Over the past few decades, cardiovascular disease and related complications have surpassed all others as the important causes of death on a universal scale. At the moment, they are the important cause of mortality universal, including in India. It is important to know how to find cardiovascular problems early so that patients get better care and prices go down. This project utilizes the UCI Heart Disease Dataset to develop ML and DL models capable of detecting cardiac diseases. Heart illness was categorized using Convolutional Neural Network (CNN) models, which are able to detect intricate patterns in supplied data. A confusion matrix rating, an F1-score, a ROC curve, accuracy, precision, and recall were some of the measures used to grade the model. It did much better than the Neural Network, Deep Neural Network (DNN), and Gradient Boosted Trees (GBT) models, with 91.71% accuracy, 88.88% precision, 82.75% memory, and 85.70% F1-score. Comparative study showed that CNN was the most accurate model. Other models had different balances between accuracy and recall. The experiment results show that the optional CNN model is a decent way to identify cardiovascular disease. This means that it could be used in healthcare systems to find diseases earlier and treat patients better.