Objective and Purpose
Self-rated health is an important indicator of overall well-being because it reflects how individuals perceive their own health, rather than relying solely on medical diagnoses. According to the Centers for Disease Control and Prevention (CDC), self-rated health is an important predictor of health outcomes, including mortality, morbidity, and functional status. Access to healthcare may play a role in these perceptions, as adults without health insurance may face greater barriers to preventive services, early diagnosis, and treatment. Routine checkups, on the other hand, provide opportunities to monitor health and identify potential concerns before they become more serious.
The objective of this geovisualization is to explore the relationship between healthcare access, preventive care, and self-rated health across U.S. counties using data from the CDC's PLACES (Population Level Analysis and Community Estimates) dataset. By examining the percentage of adults reporting fair or poor health alongside measures of health insurance coverage and routine checkups, this interactive visualization allows users to identify geographic patterns and investigate whether differences in healthcare access and utilization are associated with variations in self-rated health.
Methods
This geovisualization was developed in Tableau Public using county-level data from the CDC's PLACES dataset. Three public health indicators were selected for this project: one measure of health status and two measures related to preventive healthcare. The health status measure represents the percentage of adults reporting fair or poor self-rated health. The two preventive healthcare measures represent the percentage of adults ages 18–64 without health insurance and the percentage of adults ages 18 and older who received a routine checkup within the past year.
To examine the geographic distribution and potential relationships among these indicators, a county-level map was created to display the percentage of adults reporting fair or poor health across the United States. Two scatterplots complement the map by comparing fair or poor self-rated health with each preventive healthcare measure: lack of health insurance and routine checkups. Each point represents an individual county, allowing users to explore geographic patterns and examine how these measures relate to one another.
Interactive features were incorporated to encourage further exploration of the data. Users can filter the visualization by state, adjust the displayed ranges of the two preventive healthcare measures, select individual counties, and view detailed percentages through tooltips. These linked features allow users to examine geographic distribution of self-rated health while examining its potential relationships with healthcare access and routine checkups.
Design Decisions
A sequential yellow-to-red color scheme was used to represent fair or poor self-rated health, with lighter yellow shades indicating lower percentages and darker red shades indicating higher percentages. This color progression helps distinguish counties with different levels of self-rated health and makes geographic patterns easier to identify. County-level mapping was chosen to provide a detailed view of how self-rated health varies across the country.
Alaska and Hawaii are displayed in separate inset maps to allow the contiguous United States to occupy more space in the main map, making county-level patterns easier to see. When a user selects a state, the insets are removed and the map focuses on the selected state, providing a cleaner, more detailed view of its counties. This design maintains a broad national perspective when viewing all states while allowing users to explore individual states without unnecessary visual clutter.
Two linked scatterplots were included to explore potential relationships between self-rated health and the two preventive healthcare measures. The horizontal axes represent the percentage of adults without health insurance and the percentage of adults who received a routine checkup, respectively, while both vertical axes represent fair or poor self-rated health. Using the same health measure on both vertical axes makes it easier to compare the patterns in the two plots.
Interactivity was an important design consideration. Filtering by state updates the map and scatterplots to display the selected state's counties, while adjusting the percentage ranges narrows the counties displayed across the linked views. Selecting a county highlights the corresponding data point, helping users connect its geographic location with its position in each scatterplot. Tooltips provide the percentages for all three indicators, allowing users to access detailed information without overcrowding the map with labels.
Together, these design choices combine geographic context with statistical comparisons, allowing users to move between identifying spatial patterns and examining relationships among the indicators.
Limitations
Several limitations should be considered when interpreting this visualization. First, the percentages are age-adjusted estimates intended to support comparisons across populations with different age distributions. The indicators also apply to specific adult age groups: health insurance coverage is measured among adults ages 18–64, while routine checkups and self-rated health are measured among adults ages 18 and older. Children and other age groups outside an indicator's defined population are therefore not represented in that measure.
Second, the CDC notes that individuals may move in and out of health insurance coverage, meaning that the indicator might underestimate the prevalence of a lack of health insurance. The percentage without insurance should therefore be interpreted as an estimate rather than a complete measure of every individual's insurance history.
Another limitation is that the visualization uses county-level data rather than individual health records. The patterns observed across counties do not necessarily reflect the experiences of every person living in those areas. Additionally, relationships between the indicators do not establish cause and effect. Self-rated health and healthcare use can be influenced by other factors, including income, education, chronic health conditions, and the availability of healthcare providers.
Finally, the visualization focuses on three indicators and does not capture every aspect of healthcare access, preventive care, or community health. The results should be interpreted as an exploratory comparison of selected public health measures rather than a comprehensive assessment of county health or healthcare quality.
Data Source: PLACES Local Data for Better Health 2022
Nicole Vicenti