Social Inequality and Diabetes: A Commentary

Barnard‐Kelly, Katharine; Cherñavvsky, Daniel R.

doi:10.1007/s13300-020-00791-4

Cited by 38 publications

(49 citation statements)

References 25 publications

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“…23 As shown here, the favorable TIR effects of the COVID-19 pandemic accrued disproportionately to patients in areas with relatively high median household income and to early adopters/long-term users of the G6 System. Social inequalities in diabetes care 24 may be related to the diffusion of innovative diabetes technologies such as rtCGM. 25 …”

Section: Discussionmentioning

confidence: 99%

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range

Linden

Welsh

Hirsch

et al. 2021

Diabetes Technology & Therapeutics

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Background: The coronavirus disease 2019 (COVID-19) pandemic disrupted the lives of people with diabetes. Use of real-time continuous glucose monitoring (rtCGM) helped manage diabetes effectively. Some of these disruptions may be reflected in population-scale changes to metrics of glycemic control, such as time-in-range (TIR). Methods: We examined data from 65,067 U.S.-based users of the G6 rtCGM System (Dexcom, Inc., San Diego, CA) who had uploaded data before and during the COVID-19 pandemic. Users associated with three counties that included the cities of Los Angeles, Chicago, and New York or with five regions designated by the Centers for Disease Control and Prevention (CDC) were compared. Public data were used to associate regions with prepandemic and intrapandemic glycemic parameters, COVID-19 mortality, and median household income. Results: Compared with an 8-week prepandemic interval before stay-at-home orders (January 6, 2020, to March 1, 2020), overall mean (standard deviation) TIR improved from 59.0 (20.1)% to 61.0 (20.4)% during the early pandemic period (April 20, 2020 to June 14, 2020, P < 0.001). TIR improvements were noted in all three counties and in all five CDC-designated regions. Higher COVID-19 mortality was associated with higher proportions of individuals experiencing TIR improvements of ≥5 percentage points. Users in economically wealthier zip codes had higher pre- and intrapandemic TIR values and greater relative improvements in TIR. TIR and pandemic-related improvements in TIR varied across CDC-designated regions. Conclusions: Population-level rtCGM data may be used to monitor changes in glycemic control with temporal and geographic specificity. The COVID-19 pandemic is associated with improvements in TIR, which were not evenly distributed across the United States.

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Section: Discussionmentioning

confidence: 99%

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range

Linden

Welsh

Hirsch

et al. 2021

Diabetes Technology & Therapeutics

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“…We have previously shown that flash monitoring use is substantially lower in those with the highest levels of deprivation, 8 even in the context of universal NHS funding, and this was replicated in the current study. A similarly sharp gradient exists with respect to deprivation and CSII use 10 . Clinician preconceptions, with little supporting evidence, relating to who is likely to derive benefit from CSII, may contribute to the inequitable distribution of CSII use 20 .…”

Section: Discussionmentioning

confidence: 99%

“…C‐peptide data were available in 1661 individuals. Flash monitoring has been available on NHS prescription in our centre since February 2018 and the criteria governing eligibility are described in more detail elsewhere 10 . This project did not involve deviation from usual clinical care or access to data beyond our usual clinical IT systems and ethical approval was not required.…”

Section: Participants and Methodsmentioning

confidence: 99%

“…Clear evidence supports the glucose lowering efficacy of structured education programmes, such as ‘Dose Adjustment for Normal Eating’ (DAFNE), 5,6 CSII 6,7 and CGM/flash monitoring 7,8 . Access to these interventions, however, remains limited and skewed towards individuals with lower levels of socioeconomic deprivation 8‐10 . Glycaemic targets may be achieved with a lower risk of hypoglycaemia in individuals with retained C‐peptide secretion 11,12 .…”

Section: Introductionmentioning

confidence: 99%

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Socioeconomic deprivation, technology use, C‐peptide, smoking and other predictors of glycaemic control in adults with type 1 diabetes

et al. 2020

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Aims Intensive glycaemic control is associated with substantial health benefits in people with type 1 diabetes. We sought to examine clinical and demographic factors associated with meeting glycaemic targets in type 1 diabetes. Methods We conducted a cross‐sectional analysis of 4594 individuals with type 1 diabetes. The primary outcome of the study was assessing factors associated with meeting HbA1c targets. Secondary endpoints included factors associated with continuous subcutaneous insulin infusion (CSII) use and persistent C‐peptide secretion. Results Socioeconomic deprivation was strongly associated with a lower likelihood of achieving an HbA1c <58 mmol/mol (7.5%) (20% in the most deprived quintile vs. 40% in the least deprived, p < 0.001). In multivariate analysis, absence of smoking history (OR 3.06, p < 0.001), flash monitoring (OR 1.49, p < 0.001), CSII (1.43, p = 0.022) and longer diabetes duration (OR 1.02 per year, p = 0.004) were independently associated with achieving HbA1c <58 mmol/mol (7.5%), whereas increasing age (OR 0.99 per year, p = 0.004) and C‐peptide <50 pM (OR 0.58, p < 0.001) were associated with a lower likelihood of meeting this target. Low C‐peptide (<50 pM) was less likely in men (OR 0.55, p < 0.001) and never smokers (0.44, p < 0.001) in multivariate analysis. Conclusions Lower levels of deprivation, non‐smoking, higher C‐peptide, technology use, lower BMI and male gender were all associated with a higher likelihood of meeting HbA1c targets. Access to proven diabetes treatments is lower in the most deprived individuals. Urgent efforts are required to provide treatments which are effective across the socioeconomic gradient.

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“…Beyond policy change for reimbursement of health technologies such as CGM, disparities in access to health technologies continue to exist when access to diabetes specialists and diabetes educators is limited in areas of socioeconomic deprivation. 59 Second, by virtue of their forward-looking orientation, the capital markets and investment community have already moved forward in assigning winners and losers in the post-COVID-19 world. The winners are indisputably companies and organizations that place technology at the center of what they do-consider that over the past year, at the time of this writing, the S&P Technology Index is up 44% while the S&P 500 overall index is up 18%, and that all of the equity market growth this year has been driven by large-cap technology companies.…”

Section: Covid-19 and Health Economics S-17mentioning

confidence: 99%

Impact of COVID-19 on Health Economics and Technology of Diabetes Care: Use Cases of Real-Time Continuous Glucose Monitoring to Transform Health Care During a Global Pandemic

Garg

Norman

2021

Diabetes Technology & Therapeutics

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Background: The coronavirus disease 2019 (COVID-19) pandemic has exposed vulnerabilities and placed tremendous financial pressure on nearly all aspects of the U.S. health care system. Diabetes care is an example of the confluence of the pandemic and heightened importance of technology in changing care delivery. It has been estimated the added total direct U.S. medical cost burden due to COVID-19 to range between $160B (20% of the population infected) and $650B (80% of the population infected) over the course of the pandemic. The corresponding range for the population with diabetes is between $16B and $65B, representing between 5% and 20% of overall diabetes expenditure in the United States. We examine the evidence to support allocating part of this added spend to infrastructure capabilities to accelerate remote monitoring and management of diabetes. Methods and Results: We reviewed recent topical literature and COVID-19-related analyses in the public health, health technology, and health economics fields in addition to databases and surveys from government sources and the private sector. We summarized findings on use cases for real-time continuous glucose monitoring in the community, for telehealth, and in the hospital setting to highlight the successes and challenges of accelerating the adoption of a digital technology out of necessity during the pandemic and beyond. Conclusions: One critical and lasting consequence of the pandemic will be the accelerated adoption of digital technology in health care delivery. We conclude by discussing ways in which the changes wrought by COVID-19 from a health care, policy, and economics perspective can add value and are likely to endure postpandemic.

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Social Inequality and Diabetes: A Commentary

Cited by 38 publications

References 25 publications

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range

Real-Time Continuous Glucose Monitoring During the Coronavirus Disease 2019 Pandemic and Its Impact on Time in Range

Socioeconomic deprivation, technology use, C‐peptide, smoking and other predictors of glycaemic control in adults with type 1 diabetes

Impact of COVID-19 on Health Economics and Technology of Diabetes Care: Use Cases of Real-Time Continuous Glucose Monitoring to Transform Health Care During a Global Pandemic

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