Onset of type 1 diabetes mellitus in rural areas of the USA

Disparities in Continuous Glucose Monitor Use Between Children With Type 1 Diabetes Living in Urban and Rural Areas

OBJECTIVE

Despite evidence that continuous glucose monitoring (CGM) use is associated with lower HbA1c among children with type 1 diabetes, uptake of this technology remains lower among those with difficulty accessing health care, including those from lower socioeconomic status backgrounds and racial and ethnic minorities. In this study, we sought to explore the impact of rural location in use of CGM technology to guide patient and provider decision making.

RESEARCH DESIGN AND METHODS

In this retrospective study of electronic health record demographic and visits data from a single diabetes program from 1 January 2018 through 31 December 2021, we compared the odds of completing a visit with (+) and without (-) CGM interpretation between rural-urban commuting area (RUCA) designations.

RESULTS

Among the 13,645 visits completed by 2,008 patients with type 1 diabetes younger than age 18 years, we found children living in small rural towns had 31% lower odds (6.3% of CGM+ visits, 8.6% of CGM- visits; adjusted odds ratio [aOR] 0.69, 95% CI 0.51-0.94) and those living in isolated rural towns had 49% lower odds (2.0% of CGM+ visits, 3.4% of CGM- visits; aOR 0.51, 95% CI 0.28-0.92) of completing a CGM-billed clinic visit compared with those living in urban areas (70.0% of CGM+ visits, 67.2% of CGM- visits). We also found significant differences in CGM-billed visits by neighborhood deprivation as well as race/ethnicity and insurance payor.

CONCLUSIONS

Geographic location presents a meaningful barrier to access to care for patients living with type 1 diabetes. Further work is needed to identify and address the needs of children and families living in rural areas to improve the care of these patients.

Evaluating the Impact of Telemedicine Expansion on Visit Frequency for Children with Type 1 Diabetes at a Single Academic Center in Oregon

Objective: The telemedicine expansion (TE) that accompanied the COVID-19 pandemic presents a novel opportunity to increase access to care for rural-residing children with type 1 diabetes (T1D) who may live a great distance from their provider. The study objective was to compare trends in visit frequency among the pediatric T1D population at a single academic center in Oregon before and after TE by those living <100 miles versus ≥100 miles from clinic (MFC) and those residing in urban versus rural areas. Research Design and Methods: We evaluated electronic health record data from 790 children receiving care between July 2018 and December 2021. We estimated differences in likelihood of adequately timed monitoring care (ATMC) over time by patient residence using Generalized Estimating Equations. Results: Just before TE, 37.3% of children were receiving ATMC and those living ≥100 MFC were 20.6% less likely to receive ATMC compared with those living <100 MFC (relative risk [RR] 0.79; confidence interval [95% CI]: 0.57-1.11). Following TE, decreases in ATMC for those living ≥100 MFC were less than for those living <100 MFC (RR of interaction: 1.17; 95% CI: 0.68-2.00). Just before TE, those living in rural areas were as likely to receive ATMC compared with those living in urban areas (RR 1.00; 95% CI: 0.61-1.63). Following TE, decreases in ATMC were greater for those living in rural areas versus urban areas (RR of interaction: 0.79; 95% CI: 0.31-2.01). Conclusions: Between July 2020 and December 2021, the likelihood of ATMC decreased across the entire pediatric T1D population. Decreases in ATMC during this period were more substantial for those living <100 MFC and/or in rural areas, however, these discrepancies were not statistically significant.

Socioeconomic deprivation and cardiometabolic risk factors in individuals with type 1 diabetes: T1D exchange clinic registry

AIMS

Social determinants of health (SDOH) influence cardiovascular health in the general population; however, the degree to which this occurs in individuals with type 1 diabetes (T1D) is not well understood. We evaluated associations among socioeconomic deprivation and cardiometabolic risk factors (hemoglobin A1c, low-density lipoprotein, blood pressure, body mass index, physical activity) in individuals with T1D from the T1D Clinic Exchange Registry.

METHODS

We evaluated the association between the social deprivation index (SDI) and cardiometabolic risk factors using multivariable and logistic regression among 18,754 participants ages 13 - 90 years (mean 29.2 ± 17) in the T1D Exchange clinic registry from 6,320 zip code tabulation areas (2007-2017).

RESULTS

SDI was associated with multiple cardiometabolic risk factors even after adjusting for covariates (age, biological sex, T1D duration, and race/ethnicity) in the multivariable linear regression models. Those in the highest socially deprived areas had 1.69 (unadjusted) and 1.78 (adjusted) times odds of a triple concomitant risk burden of poor glycemia, dyslipidemia, and hypertension.

CONCLUSIONS

Persistent SDOH differences could account for a substantial degree of poor achievement of cardiometabolic targets in individuals with T1D. Our results suggest the need for a broader framework to understand the association between T1D and adverse cardiometabolic outcomes.

Is Population Density Associated with Non-Communicable Disease in Western Developed Countries? A Systematic Review

Over the last three decades, researchers have investigated population density and health outcomes at differing scale. There has not been a systematic review conducted in order to synthesise this evidence. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, we systematically reviewed quantitative evidence published since 1990 on population density and non-communicable disease (NCD) within Westernised countries. Fifty-four studies met the inclusion criteria and were evaluated utilising a quality assessment tool for ecological studies. High population density appears to be associated with higher mortality rates of a range of cancers, cardiovascular disease and COPD, and a higher incidence of a range of cancers, asthma and club foot. In contrast, diabetes incidence was found to be associated with low population density. High and low population density are therefore risk markers for a range of NCDs, indicating that there are unidentified factors and mechanisms underlying aetiology. On closer examination, our synthesis revealed important and complex relationships between population density, the built environment, the nature of greenspace and man-made exposures. In light of increasing rates of morbidity and mortality, future research is required to investigate these associations in order to establish causative agents for each NCD.

Glycemic outcomes among rural patients in the type 1 diabetes T1D Exchange registry, January 2016-March 2018: a cross-sectional cohort study

INTRODUCTION

Does rural status influence glycemic outcomes among participants in the type 1 diabetes T1D Exchange clinic registry?

RESEARCH DESIGN AND METHODS

Data from the T1D Exchange clinic registry between January 2016 and March 2018 were identified by rural-urban status and stratified by age and hemoglobin A1c (HbA1c). Multivariable regression modeling was performed to isolate HbA1c differences. A full model including all significant (p<0.05 via two-sided testing) differential factors was determined with an additional indicator for rural status, and adjusted for duration of diabetes, use of continuous glucose monitoring device, age, race/ethnicity, and private insurance status. The model was reduced using backwards elimination stepwise procedures until only significant factors remained.

RESULTS

Mean HbA1c levels for all rural participants were significantly higher (8.71%; 72 mmol/mol) compared with the urban group (8.48%; 69 mmol/mol), p<0.001. For youth under 13 years of age, rural participants had a higher mean HbA1c (8.65%; 71 mmol/mol) compared with urban (8.45% 69 mmol/mol), p=0.022. Rural youth (13-<18 years) had a higher mean HbA1c (9.39%; 79 mmol/mol) than urban youth (9.14%; 76 mmol/mol), p<0.001. Rural young adults (18-<26 years) had a higher mean HbA1c (9.07%; 76 mmol/mol) than urban young adults (8.88%; 74 mmol/mol), p=0.042. Rural adults (≥26 years; n=589) were the only group that did not have a higher mean HbA1c (7.76%, 61.3 mmol) than urban adults (n=4770; 7.72%, 60.9 mmol/mol), p=0.503. Rural locale was highly significant (beta=0.175, p<0.001) despite controlling for potentially confounding differences between rural and urban groups.

CONCLUSIONS

Among this T1D Exchange cohort, there is a pattern of higher mean HbA1c being associated with rural status, even after adjustment for characteristic differences, most strikingly among those under 26 years of age. This disparity and contributing factors need to be more thoroughly studied to provide effective solutions.