Exploring Correlations in Public Health and Social Factors: A Case Study from Indiana

Working Paper Abstract:
This paper presents a detailed analysis of a health and well-being dataset from Indiana, exploring significant correlations between various public health and socio-economic factors. The study identifies key relationships between responses to survey questions, offering insights into the interconnected nature of health, economic, and social challenges in Indiana.

Introduction:
Public health research necessitates an understanding of various factors beyond medical ones, including socio-economic and environmental influences. This paper examines a dataset from Indiana, sourced from [Indiana Management Performance Hub (2021). Hoosier Health and Well-being by County and Date. Retrieved from https://hub.mph.in.gov/dataset/hoosier-health-and-well-being-by-county-and-date/resource/033d45a3-b9a4-4b6d-86f4-ecdd06c5b7d5?inner_span=True], to analyze correlations between responses to diverse health and social-related survey questions. The aim is to unearth significant patterns that could inform and enhance public policy and targeted health interventions.

Methodology:
The dataset comprises responses on various health and social factors across Indiana counties. Correlation analysis was employed to identify significant relationships between responses to different survey questions. Particular focus was given to strong positive correlations (coefficients above 0.5), with an aim to understand the implications and underlying societal patterns.

Results and Discussion:

1. Transportation Barriers and Lack of Exercise (Q6 and Q10): A striking correlation (0.97) was found between difficulties in accessing transportation for healthcare and not engaging in regular exercise. This suggests that geographic or demographic barriers not only impede healthcare access but also affect physical activity. The overlap indicates a segment of the population that may be significantly disadvantaged in terms of both healthcare access and opportunities for maintaining physical health through exercise. This finding is pivotal in understanding how transportation infrastructure and public health initiatives need to be closely aligned.

      2. Financial Instability and Health Literacy (Q2 and Q7):
      The strong correlation (0.96) between experiences of utility shut-offs and needing help with reading hospital materials points to a broader narrative of financial instability impacting health literacy. This relationship highlights a demographic that struggles with both economic security and navigating the healthcare system, suggesting that financial aid programs might need to be coupled with educational initiatives to improve health literacy.

        3. Child Care and Housing Instability (Q4 and Q3):
        The observed correlation (0.95) between child care difficulties and housing instability speaks to the complex challenges facing families. Those struggling to secure child care are often the same individuals concerned about stable housing. This intersection suggests that policies aimed at assisting with child care could have a broader impact, potentially alleviating some of the stresses related to housing insecurity.

        4. Employment Uncertainty and Housing Concerns (Q9 and Q3): The correlation of 0.95 between active job seeking and worries about housing stability underscores a critical link between employment and housing security. This connection reflects a reality where job insecurity directly feeds into fears of losing one’s home. It suggests that employment support services should not only focus on job placement but also consider the housing needs of individuals. Strengthening job security could have a ripple effect, reducing the anxiety related to housing instability and potentially leading to more stable communities.

        5. Personal Safety and Healthcare Understanding (Q8 and Q7):
        A correlation of 0.94 reveals a significant overlap between individuals with safety concerns in their living environments and those facing challenges in understanding healthcare information. This finding suggests that individuals in unsafe living conditions may also be those who struggle with health literacy, indicating a compounded vulnerability. It highlights the necessity of addressing safety in living environments as part of a holistic approach to healthcare education and access. Improving living conditions could be a pivotal step in enhancing overall health literacy and access to healthcare.

        Conclusion:
        The analysis of the Indiana dataset reveals intricate correlations between social, economic, and health-related factors, emphasizing the interconnected nature of these challenges. These findings underscore the need for comprehensive, integrated approaches in public health policy and program development. Addressing these interconnected challenges holistically could lead to more effective and sustainable improvements in public health outcomes.

        References:

        • Indiana Management Performance Hub. (2021). Hoosier Health and Well-being by County and Date.


        Summary of the Indiana Health and Well-being Dataset

        Dataset Overview:
        The dataset, sourced from the Indiana Management Performance Hub, provides a comprehensive view of health and well-being metrics across various counties in Indiana. It contains a range of data collected through surveys, reflecting diverse aspects of public health, socio-economic conditions, and environmental factors impacting the residents of Indiana.

        Data Structure:

        • Temporal Scope: The dataset includes data points collected over various months and years, providing a temporal dimension to analyze trends and changes over time.
        • Geographic Scope: Data is segmented by county, allowing for a granular analysis of regional differences and similarities within the state.
        • Content: The dataset includes responses to numerous survey questions, each capturing a specific aspect of health or social well-being. These questions cover topics such as healthcare access, exercise habits, economic stability, housing security, child care challenges, and more.

        Key Features:

        • Survey Questions: Each entry in the dataset corresponds to a specific survey question, with short and long descriptions providing context about the nature of the question.
        • Response Counts: For each question, the dataset records counts of responses, offering quantitative insights into the prevalence of various health and social issues.
        • Timestamps: The inclusion of timestamps for data entry (ETL_RUN_TIMESTAMP) ensures traceability and aids in analyzing the data’s chronological development.

        Significance:
        This dataset is a valuable resource for understanding the multifaceted nature of public health and social well-being in Indiana. It offers a foundation for identifying correlations between different health and socio-economic factors, which is crucial for developing targeted interventions and informed public policy decisions.

        Data Source: