BCMS Medical Record Fall 2020 - 17

indicated massive disparities in the United States, such as the fact
that Hispanic and Latino persons are being hospitalized at nearly 5
times the rate of non-Hispanic White persons (Figure 2)35.

understanding of some of the mechanisms by which obesity worsens
the clinical course and outcomes of COVID-19, such as respiratory
compromise, inflammation, and type 2 diabetes, physicians
can better treat people of size. Though many questions remain
unanswered, as randomized clinical studies are not easily performed
in the midst of an evolving pandemic, we must keep learning so we
can take care of our most vulnerable populations. Although the most
pressing issue in the short term for Berks County is protecting its
residents from contracting and suffering from COVID-19, the focus
for our county and beyond needs to be what can be done to reverse
rising trends in obesity and diabetes as well as other steps to lessen
the impact of future outbreaks.

Works Cited

Figure 2: Age-adjusted COVID-19-associated hospitalization rates
by race and ethnicity, COVID-NET, March 1 - August 8, 202035.
After adjusting for age, Hispanic or Latino persons, Non-Hispanic Black
persons, and Non-Hispanic American Indian or Alaska Native persons are
all hospitalized from COVID-19 between 4.7 and 5.0 times the rate of
Non-Hispanic White persons nationwide as of August 8, 2020. By the same
measures, Non-Hispanic Asian or Pacific Islander persons are hospitalized
from COVID-19 at a rate about 30% higher than non-Hispanic White
persons.

Regarding the extent of COVID-19 disparities in Reading-a
city already more conducive to the spread of COVID-19 as an
urban setting with more crowding-Toledo further states that
"We know where the disparities are in our community. Those most
vulnerable are dealing with a number of barriers: language, access
to quality health care and transportation can all be problems," and
additionally, "When you look at where the COVID-19 positive
cases are, it overlaps in exactly the same neighborhoods that are
at risk of other diseases. That should tell you something."33 Since
over two-fifths of Berks COVID-19 cases are in the 19601, 19602,
and 19604 zip codes1-which cover much of Reading-Toledo's
observation supports how other factors contribute to Berks County's
higher prevalences of interconnected diseases such as obesity,
type 2 diabetes, and COVID-19. To temporarily mitigate these
issues for Berks County's most vulnerable populations with regard
to managing COVID-19, leaders and physicians in Berks must
continue to educate about and encourage the practices of social
distancing, mask wearing, and hand washing. Since these strategies
still put responsibility on those who are most negatively affected by
social conditions, other efforts that expand contact tracing, testing,
quarantining, and data collection must be supported until even
larger changes are made to address the roots of structural issues.

1. Pennsylvania State Department of Health. (2020). COVID-19
Data for Pennsylvania. [Data file]. Retrieved from https://www.
health.pa.gov/topics/disease/coronavirus/Pages/Cases.aspx
2. Pennsylvania State Data Center. (2019). 2018 County Total
Population Estimates Released. Retrieved from https://pasdc.hbg.psu.
edu/sdc/pasdc_files/researchbriefs/Apr_2019_CntyEst18.pdf
3. Brudereck, J. (2012, March 9). Reading area 10th in obesity rate.
Reading Eagle. Retrieved from http://www2.readingeagle.com/article.
aspx?id=369992
continued on next page >

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BCMS Medical Record Fall 2020

Table of Contents for the Digital Edition of BCMS Medical Record Fall 2020

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