Urban–Rural Differences in Health Care Utilization and COVID-19 Outcomes in Patients With Type 2 Diabetes

Annemarie G. Hirsch, PhD; Cara M. Nordberg, MPH; Karen Bandeen-Roche; Jonathan Pollak, MPP; Melissa N. Poulsen, PhD; Katherine A. Moon, PhD; Brian S. Schwartz, MD

Disclosures

Prev Chronic Dis. 2022;19(7):e44

Abstract and Introduction

Abstract

Introduction: Two studies in Pennsylvania aimed to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between type 2 diabetes (hereinafter, diabetes) and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic.

Methods: The hospitalization study evaluated a retrospective cohort of patients hospitalized with COVID-19 through 2020 for COVID-19 outcomes: death, intensive care unit (ICU) admission, mechanical ventilation, elevated D-dimer, and elevated troponin level. We used adjusted logistic regression models, adding interaction terms to evaluate effect modification by community type (township, borough, or city census tract) and CSD. The utilization study included patients with diabetes and a clinical encounter between 2017 and 2020. Autoregressive integrated moving average time-series models evaluated changes in weekly rates of emergency department and outpatient visits, hemoglobin A_1c (HbA_1c) laboratory tests, and antihyperglycemic medication orders from 2018 to 2020.

Results: In the hospitalization study, of 2,751 patients hospitalized for COVID-19, 1,020 had diabetes, which was associated with ICU admission and elevated troponin. Associations did not differ by community type or CSD. In the utilization study, among 93,401 patients with diabetes, utilization measures decreased in March 2020. Utilization increased in July, and then began to stabilize or decline through the end of 2020. Changes in HbA_1c tests and medication order trends during the pandemic differed by community type and CSD.

Conclusion: Diabetes was associated with selected outcomes among individuals hospitalized for COVID-19, but these did not differ by community features. Utilization trajectories among individuals with diabetes during the pandemic were influenced by community type and CSD and could be used to identify individuals at risk of gaps in diabetes care.

Introduction

Despite early concerns of elevated risk of COVID-19 infection in urban communities,^[1] studies of infection rates adjusted for socioeconomic factors have shown either no differences or reduced risks between urban and rural areas.^[2] Urban communities have also been found to have lower risk of severe COVID-19 outcomes,^[3] attributed to multiple factors, including better access to health care, healthy food, and walkable environments that reduce the risk of severe COVID-19 outcomes.^[3,4] These same mechanisms may also mitigate risk of severe COVID-19 associated with type 2 diabetes (hereinafter, diabetes).

Reports of associations between diabetes and COVID-19 outcomes have been mixed. Some studies have reported associations with severe COVID-19 (eg, intensive care unit [ICU] admission) and postacute COVID-19 sequelae,^[5–7] while others have not.^[8,9] Conversely, most, but not all, studies have reported no association between diabetes and COVID-19 mortality.^[5,6,9–11] These differences may be due to variation in study design^[12] or in study settings from diverse locations around the world. The extent to which community features modify associations between diabetes and COVID-19 outcomes remains unexplored.

The impact of COVID-19 on individuals with diabetes goes beyond COVID-19 infection. Mitigation strategies during the pandemic (eg, suspension of nonurgent care, stay-at-home orders) resulted in diabetes care disruptions.^[13,14] Health systems serving urban communities have been better able to adapt to COVID-19 mitigation strategies through telehealth technology.^[15] Thus, gaps in care could be exacerbated in rural communities, which are more likely to have limited access to broadband internet service and greater distances to clinical care settings. The objectives of this study, conducted in geographically diverse communities across 37 Pennsylvania counties, were to determine whether community type and community socioeconomic deprivation (CSD) 1) modified associations between diabetes and COVID-19 hospitalization outcomes, and 2) influenced health care utilization among individuals with diabetes during the COVID-19 pandemic.

1 2 3 4

Next Section

Abstract and Introduction
Methods
Results
Discussion
References
Appendix
Sidebar

Table 1. Selected Characteristics of Individuals Hospitalized With COVID-19 Through December 31, 2020, by Type 2 Diabetes Status, Pennsylvania ^a
Variable	Type 2 diabetes, n = 1,020 (37.1%)	No type 2 diabetes, n = 1,731 (62.9%)
Sociodemographics and habits
Age at first hospitalization, mean (SD), y	69.9 (13.2)	65.6 (19.4)
Sex, female	467 (45.8)	841 (48.6)
Race, Black	40 (3.9)	89 (5.1)
Hispanic	70 (6.9)	131 (7.6)
Medical Assistance, >0% of time	139 (13.6)	187 (10.8)
Institutionalized housing	144 (14.1)	168 (9.7)
Tobacco use, ever	555 (54.4)	761 (44.0)
Selected outcomes
Died in hospital	198 (19.4)	260 (15.0)
Died after hospital	34 (3.3)	71 (4.1)
Deceased total	232 (22.8)	331 (19.1)
Admitted to intensive care unit	277 (27.2)	373 (21.6)
Required mechanical ventilation	137 (13.4)	205 (11.8)
Hospital readmissions	65 (6.4)	87 (5.0)
Selected comorbid conditions
Chronic kidney disease	417 (40.9)	348 (20.1)
Chronic lung disease	217 (21.3)	229 (13.2)
Selected laboratory measurements
Troponin, plasma, any hospitalization^b
Missing	127 (12.5)	324 (18.7)
Elevated level	606 (59.4)	740 (42.8)
Maximum value, mean (SD)	92.6 (441.4)	62.2 (325.8)
D-dimer, plasma, any hospitalization
Missing	197 (19.3)	420 (24.3)
≥0.5 μg/mL	723 (70.9)	1,156 (66.8)
Maximum value, mean (SD)	3.28 (4.77)	3.02 (4.49)
Community measures
Residential location by administrative community type
Township	490 (48.0)	891 (51.5)
Borough	302 (29.6)	499 (28.8)
City census tract	228 (22.4)	341 (19.7)
CSD quartiles
1st (least disadvantaged)	166 (16.3)	337 (19.5)
2nd	202 (19.8)	374 (21.6)
3rd	297 (29.1)	500 (28.9)
4th (most disadvantaged)	355 (34.8)	520 (30.0)

Abbreviation: CSD, community socioeconomic disadvantage.
^aData are shown as n (%) unless otherwise indicated.
^bCut-point for elevated troponin level differs by sex: men, 22 ng/L; women, 14 ng/L.

Table 2. Associations of Type 2 Diabetes Status With 5 Hospitalization Outcomes for COVID-19 Through December 31, 2020, Pennsylvania ^a,b
Variable	Death, total vs not deceased^c (n = 2,751)	ICU, any vs not (n = 2,751)	Ventilator, any vs none (n = 2,751)	Troponin ≥22 ng/L vs lower (n = 1,346)	D-dimer ≥0.5 μg/mL vs lower (n = 1,879)
Model 1: base model
Sex, female vs male	0.77 (0.63–0.95)	0.76 (0.63–0.93)	0.85 (0.66–1.10)	1.31 (1.12–1.53)	0.83 (0.71–0.98)
Race and ethnicity
Non-White vs White	0.56 (0.35–0.89)	0.62 (0.44–0.87)	0.83 (0.55–1.27)	1.02 (0.70–1.49)	0.93 (0.69–1.26)
Hispanic vs non-Hispanic	0.54 (0.28–1.05)	0.79 (0.54–1.14)	1.03 (0.66–1.61)	0.54 (0.35–0.82)	1.06 (0.76–1.47)
Medical Assistance, >0% time vs no time	1.39 (0.95–2.04)	1.02 (0.76–1.37)	0.90 (0.60–1.35)	1.25 (0.90–1.73)	1.28 (0.95–1.71)
Time period for hospitalization (2020)^d
Middle months vs early months	0.51 (0.35–0.75)	1.13 (0.82–1.57)	0.35 (0.22–0.55)	0.70 (0.51–0.96)	0.53 (0.39–0.72)
Late months vs early months	0.49 (0.40–0.62)	0.50 (0.40–0.62)	0.43 (0.33–0.56)	0.76 (0.61–0.96)	0.80 (0.63–1.03)
Type 2 diabetes	1.15 (0.94–1.41)	1.21 (1.01–1.45)	1.06 (0.85–1.32)	1.87 (1.56–2.25)	0.96 (0.80–1.15)
Models 2a–e: adjusted associations of new variables added one at a time to base model
2a. Chronic kidney disease vs none	1.46 (1.18–1.80)	1.00 (0.80–1.24)	1.04 (0.84–1.46)	2.60 (2.10–3.23)	0.95 (0.78–1.15)
2b. Chronic lung disease vs none	1.35 (1.06–1.73)	1.10 (0.87–1.38)	1.07 (0.79–1.43)	1.64 (1.29–2.09)	0.99 (0.78–1.25)
2c. Institutionalized vs not	1.63 (1.23–2.16)	1.04 (0.77–1.42)	1.14 (0.77–1.69)	2.23 (1.67–2.97)	0.92 (0.70–1.22)
2d. CSD, 1st vs 4th quartile (least versus most deprived)	0.74 (0.54–1.01)	0.85 (0.64–1.14)	0.96 (0.66–1.39)	0.79 (0.61–1.02)	0.97 (0.73–1.29)
2e. Administrative community type
Borough vs township	0.92 (0.73–1.15)	1.03 (0.81–1.31)	1.12 (0.85–1.49)	1.18 (0.94–1.48)	0.80 (0.64–1.01)
City census tract vs township	1.05 (0.78–1.40)	0.81 (0.63–1.05)	0.88 (0.65–1.20)	0.96 (0.76–1.21)	0.85 (0.66–1.08)
Models 3 and 4: fully adjusted diabetes associations (model 3: CKD and CLD added to base model; model 4: institutionalized added to Model 3)
3. Type 2 diabetes vs none	1.05 (0.85–1.29)	1.21 (1.003–1.45)	1.04 (0.83–1.30)	1.57 (1.30–1.90)	0.97 (0.78–1.16)
4. Type 2 diabetes vs none	1.02 (0.83–1.25)	1.21 (1.0004–1.45)	1.03 (0.82–1.30)	1.54 (1.28–1.86)	0.97 (0.80–1.17)

Abbreviations: CKD, chronic kidney disease; CLD, chronic lung disease; CSD, community socioeconomic deprivation; ICU, intensive care unit.
^aAdjusted for age: linear, quadratic, and cubic.
^bAll data are shown as odds ratio (95% CI).
^cDeath total = death during and after hospitalization.
^dTime period: early (March to May); middle (June to September); late (October to December), all in 2020.

Table 3. Selected Characteristics of Individuals With Type 2 Diabetes Who Had an Encounter at Geisinger Between 2018 and 2020, by Measurement Year, Pennsylvania ^a,b
Variable	Full cohort (N = 93,401)	2018 cohort (n = 81,393)	2019 cohort (n = 85,812)	2020 cohort (n = 87,612)
Sociodemographics
Age, mean (SD), y	57.0 (14.4)	56.8 (14.2)	56.6 (14.2)	56.4 (14.2)
Sex, female	44,897 (48.1)	39,538 (48.6)	41,507 (48.4)	42,269 (48.2)
Race, non-White	5,993 (6.4)	4,592 (5.6)	5,364 (6.2)	5,822 (6.6)
Hispanic	3,962 (4.2)	3,159 (3.9)	3,606 (4.2)	3,854 (4.4)
Medical assistance, >0% of time	12,898 (13.8)	10,857 (13.3)	11,786 (13.7)	12,390 (14.1)
Community measures
Residential location by administrative community type
Township	51,564 (55.2)	45,181 (55.5)	47,461 (55.3)	48,337 (55.2)
Borough	27,302 (29.2)	23,800 (29.2)	25,034 (29.2)	25,587 (29.2)
City census tract	14,535 (15.6)	12,412 (15.2)	13,317 (15.5)	13,688 (15.6)
Community socioeconomic deprivation quartiles
1st (least deprived)	19,634 (21.0)	17,204 (21.1)	18,132 (21.1)	18,478 (21.1)
2nd	21,674 (23.2)	18,941 (23.3)	19,936 (23.2)	20,383 (23.3)
3rd	25,954 (27.8)	22,504 (27.6)	23,757 (27.7)	24,262 (27.7)
4th (most deprived)	26,139 (28.0)	22,744 (27.9)	23,987 (28.0)	24,489 (28.0)

^aIndividuals were included in measurement year if they were alive at the start of the year and met type 2 diabetes criteria by the end of the year.
^bData are shown as n (%) unless otherwise indicated.

Appendix

Appendix Figure 1 and Appendix Figure 2 are available at https://www.geisinger.edu/research/departments-and-centers/environmental-health-institute/diabetes.

Number and Proportion of Participant Addresses in Administrative Community Types in Each of the US Census Bureau Categories^a
US Census Bureau categories	Township	Borough	City census tract
Median population density, per square mile	62	1,713	5,537
Rural, n	32,153	2,979	30
Column %	62.4	10.9	0.21
Row %	91.4	8.4	0.09
Urban cluster, n	8,572	9,945	2,948
Column %	16.6	36.4	20.3
Row %	39.9	46.3	13.7
Urbanized area, n	10,839	14,378	11,557
Column %	21.0	52.7	79.5
Row %	29.5	39.0	31.4
^aThe row percent reflects the percentage of each of the 3 rows: rural, urban, urbanized cluster. Among people living in rural areas, for example, 91.4% live in townships, 8.4% live in boroughs, and 0.09% live in city census tracts. The column percent reflects the percentage of each of the 3 columns: townships, boroughs, city census tracts. In the townships column, for example, 62.4% of townships are rural, 16.6% of townships are in urban clusters, and 21.0% of townships are in urbanized areas.