Thursday, December 2, 2021

Rates of Smoking and Social Associations Predict PA County COVID Case Mortality

Two weeks ago I looked at the correlation between COVID case mortality and Trump's % of the vote in 2020 for Pennsylvania counties and six sub measures used to determine County Health Rankings.  The measure that was most strongly associated with COVID case mortality was the health behavior z-score (a higher z score is worse) accounting for 6.9% of the variability.  Health behaviors was even more strongly associated with Trump's % of the vote as shown in the above graph accounting for 34.4% of the variability.  This association would be even stronger if Philadelphia were excluded.  This post will focus on the individual statistics used to determine the sub measures and their association with COVID Case Mortality.  The mortality rates occur on top of the the other health issues confronting each county.

The above graph shows the strongest univariate association for the number of social membership associations per 100,000 and COVID Case mortality.  This relationship accounts for 20.4% of the variability.  This measure is not a component of the health behaviors sub measure.  It is a component of the social and economic measure.  The number of social associations is weakly correlated with health behaviors, accounting for 4.9% of the variability.

The next strongest variable associated with COVID Case Mortality is the average number of mentally unhealthy days (as reported to the Behavioral Risk Factor Surveillance System).  This measure accounted for 18.6% of the variability.  This measure is a component of the quality of life sub measure.

The percentage of smokers in the county is positively associated with the COVID case mortality rate accounting for 11.9% of the variability.  This measure is part of the health behaviors sub measure. 

Access to exercise opportunities is negatively correlated with COVID case mortality with counties having higher mortality rates generally having lower access to exercise opportunities.  This and the other graphs have outliers.  If a correlation were perfect positive or negative, all of the counties would form a perfect straight line sloping upward or downward.  

As always, one should be careful about inferring cause and effect relationships.  These statistics from County Health Rankings were compiled before the coronavirus pandemic began.  Next week I will look at the association of county health ranking measures with Trump's % of the vote.

**Related Posts**

The Seven Counties in PA that are Worse than Cambria in COVID Case Mortality