I have looked at Unmet Need Scores (UNS) in Pennsylvania and the Alleghenies. The UNS is a composite of dozens of related health, social and economic variables. Teasing apart the relationships among the variables one by one is tricky. There is a method that allows for identifying clusters of highly correlated variables called factor analysis. This allows us to identify underlying health factors in Pennsylvania and in the Alleghenies.
Pennsylvania
The above graph shows the 2 strongest factors found in the Pennsylvania data set. The first factor on the vertical axis runs from -1 to +1. Variables close to the extreme ends of the scale are more highly correlated with each other than the ones at the middle of the scale. We see that at the positive end of the scale are the variables smoking, obesity, poor physical and mental health, asthma and diabetes. At the negative end of the scale are dental visits, having an associate degree or higher, pap smear and cervical cancer screening and broadband access. These variables taken together appear to form a health behaviors factor that accounts for 32% of the variability in Pennsylvania’s data.
A separate cluster of correlated variables was extracted accounting for 10% of the variability. The variables at the positive end are all cause mortality, drug mortality, preventable hospital stays, and preterm births. This means that as one of the variables increases, the others are likely to increase. At the negative end of the scale is life expectancy. This means that as life expectancy increases, the variables at the positive end of the scale are likely to decrease. The variables at the zero point have no effect on either factor.
The Alleghenies
I also have a separate data set for the Alleghenies from the HRSA data tool. The above graph shows the top 2 factors for the Alleghenies. The first factor has the same factors as the whole state: smoking, obesity, poor physical and mental health, asthma and diabetes. At the negative end of the scale are the variables: dental visits, having an associate degree or higher, and cervical cancer screening. Broadband access and pap smears did not load as heavily for the Alleghenies as they did for the whole state. This factor appears to represent health behaviors and accounts for 29% of the variability.
The same factors load on the 2nd factor for the Alleghenies and Pennsylvania and account for 12% of the variance. At the positive end: all-cause mortality, drug mortality, preventable hospital stays, and preterm births while life expectancy is at the negative end. This factor is also a mortality factor. These health factors in Pennsylvania and the Alleghenies interact in a similar manner with a few small differences.
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