Health service inequalities during the COVID-19 pandemic among elderly people living in large urban and non-urban areas in Florida, US
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Abstract
Objectives
Health inequalities were often exacerbated during the emerging epidemic. This study examined urban and non-urban inequalities in health services among COVID-19 patients aged 65 or above in US Florida from March 2 to May 27, 2020.
Methods
A retrospective time series analysis was conducted using individual patient records. Multivariable Poisson and logistic models were used to calculate adjusted incidence of COVID-19 and the associated rates of emergency department (ED) visits, hospitalizations and deaths.
Results
As of May 27, 2020, there were 13,659 elderly COVID-19 patients (people aged 65 or above) in Florida and 14.9% of them died. Elderly people living in small metropolitan areas might be less likely to be confirmed with COVID-19 infection than those living in large metropolitan areas. The ED visit and hospitalization rates decreased significantly across metropolitan statuses for both men and women. Those patients living in small metropolitan or rural areas were less likely to be hospitalized than those living in large metropolitan areas (35% and 34% versus 41%). Elderly women aged 75 or above living in rural areas had 113% higher adjusted incidence of COVID-19 than those living in large metropolitan areas, and the rates of hospitalizations were lower compared with those counterparts living in large metropolitan areas (29% versus 46%; OR: 0.37 [0.25-0.54]; p <0.001).
Conclusions
For elderly people living in US Florida, those who living in small metropolitan or rural areas were less likely to receive adequate health care than those who living in large or medium metropolitan areas during the COVID-19 pandemic.
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SciScore for 10.1101/2020.05.01.20087791: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study had some limitations. First of all, not all patient’s information was publicly released due to privacy concerns. There were no explicit and accurate dates of symptom onset, clinic or ED visits, hospitalizations, and deaths for each patient. Therefore, we were only able to use logistic regressions to model the …
SciScore for 10.1101/2020.05.01.20087791: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study had some limitations. First of all, not all patient’s information was publicly released due to privacy concerns. There were no explicit and accurate dates of symptom onset, clinic or ED visits, hospitalizations, and deaths for each patient. Therefore, we were only able to use logistic regressions to model the cumulative incidence of the ED visits, hospitalizations and deaths among those diagnosed with COVID-19. In addition, there was no information such as race and ethnicity, income and education levels in the file, hindering our ability to fully explore the roots of disparities (Hill et al. 2015) and precluding us from examine causalities of these health service inequalities. However, this problem was not unique to Florida. Many other states released aggregated data only. To some extent, we had more than enough data that were useful to paint a broad picture, but no good data to help us understand the drives of epidemic process and examine health disparities behind the case counts. Second, this study was based on the existing data on the confirmed and reported cases, thus lacked people who were infected with virus but not reported (possibly asymptomatic or mild symptomatic). This may bias our results. Although elderly patients might be more likely to have symptoms if infected by the virus, we would nevertheless miss many asymptomatic or mildly symptomatic patients who would not seek care or not be detected. We did not know whether the proportion of asymptomatic pat...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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