Mental Health Illness Analysis

About the project

Mental health is a topic of immense interest and importance to me, which is why I embarked on this project to analyze relevant data. As someone who is passionate about promoting mental wellness and addressing mental health stigma, I was excited to undertake this endeavor and gain a deeper understanding of the subject. I firmly believe that mental health is a critical component of overall well-being, and it's essential to have accurate and comprehensive data to guide our efforts in promoting and supporting mental health. Through this analysis, I aim to contribute to the ongoing conversation about mental health and help uncover insights that can inform future policies and interventions.

Summary

The analysis of mental health data revealed several insights, including higher rates of depression and anxiety among young adults, mental health disparities among marginalized communities, and increasing rates of suicidal ideation among females. It was also discovered that the rate of mental health illnesses among females is nearly double that of males. This analysis identified the most important factors contributing to mental health illness

Objective

  1. Collect and prepare the 17 years of the USA mental health illness data (1990 to 2017).

  2. Combine, clean, and process the dataset to get ready for analysis.

  3. Analyze the dataset, and visualize using Power BI and R programming

  4. Share the conclusion of this analysis to help guide the development of effective and targeted interventions to promote mental health and well-being.

    Visualization

Key Findings

  1. The analysis showed that the rate of mental health illness has gradually increased over a period of 17 years, with a significant 24.61% increase observed in 2017 when compared to rates in 1990

  2. The rate of females experiencing mental health illnesses is approximately double that of males.

  3. The analysis found that people within the age range of 20-24 years old are the most affected by mental health illnesses

  4. Based on the analysis, the three factors that exert the greatest influence in contributing to depression are drug disorders, anxiety disorders, and eating disorders.

  5. The analysis identified a strong positive correlation between drug disorder and depression, indicating that drug disorder is the most influential factor contributing to depression.