Health Issues More Pronounced in the Alleghenies

Above is a graph showing the correlation between the % of poor mental health and the % with asthma in zip codes for the states of NY, PA, MD, WV, and VA. The data is from the Health Resources and Services Administration (HRSA) Unmet Need Score map tool. The panel on the right shows zip codes in the Allegheny Mountains for either the Allegheny Mountains or the Allegheny Plateau. The panel on the left shows the zip codes that are outside the Alleghenies while the panel on the right is for zip codes in the Alleghenies. The Alleghenies are defined as the southwestern tier counties in New York, the central and western counties in Pennsylvania (excluding Erie County), the western counties of Maryland, the entire state of West Virginia, and the Western border counties of Virginia. It shows that health issues are more pronounced in the Alleghenies.

For the Alleghenies and outside, there is a positive correlation between asthma and poor mental health. This means that as the asthma rates increase in a zip code, the poor mental health rates likewise increase in that zip code. The graph shows that there is a stronger relationship between the variables in the Alleghenies vs. outside because the zip codes in the Alleghenies cluster together more tightly.

Factor Analysis

These are 2 of the more than 30 variables in the HRSA data set. A factor analysis was done to identify clusters of the most highly correlated items. For the Alleghenies the first factor extracted accounts for 43.4% of the variability in the data.

The table below shows that poor mental health and asthma are the most correlated variables followed by having a dental visit with a negative value. The negative number in the table means that as the % with asthma and poor mental health increases, the % with a recent visit to a dentist decreases. All of the other factor numbers highlighted in bold in the table below are positive except for life expectancy. As the other positive factors increase such as mortality, life expectancy decreases. The values in the columns range from -1 to +1. The further away from zero they are the more influential they are in the factor.

The strongest factor extracted from outside the Alleghenies accounts for 33% of the variance for these states. Many of the variables in the table are the same but their values are generally smaller. Poor mental health has a loading of 0.776 outside the Alleghenies while it is 0.913. Poor physical health loads most strongly outside of the Alleghenies with a value of 0.890. This value is exactly the same in the Alleghenies.

The second factor extracted for the Alleghenies was poverty which explained 9.3% of the variance. The variables with the highest values on it were the % of the population in poverty and the % within 200% of the poverty level.

The second factor extracted for outside of the Alleghenies was isolation which accounted for 12.2% of the variance. The variables with the highest values on it were linguistic isolation (0.796), population size (0.701) and no vehicle access (0.644). As one of these variables increases, the others are likely to increase in the zip codes outside of the Alleghenies in these states. The Alleghenies are more sparsely populated.

That the top 2 factors in the Alleghenies account for a larger percentage of the variance (52.7%) than for those zip codes outside (45.2%) (as well as the loadings being larger there) indicates that health factors are more pronounced in the Alleghenies.