Assessing the association of diabetes self-management education centers with age-adjusted diabetes rates across U.S.: Aspatial cluster analysis approach

Geographic disparities and temporal changes of diabetes-related mortality risks in Florida: a retrospective study

Background

Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and diabetes prevalence, little is known about disparities of DRMR in Florida. Understanding these disparities is important for guiding control programs and allocating health resources to communities most at need. Therefore, the objective of this study was to investigate geographic disparities and temporal changes of DRMR in Florida.

Methods

Retrospective mortality data for deaths that occurred from 2010 to 2019 were obtained from the Florida Department of Health. Tenth International Classification of Disease codes E10-E14 were used to identify diabetes-related deaths. County-level mortality risks were computed and presented as number of deaths per 100,000 persons. Spatial Empirical Bayesian (SEB) smoothing was performed to adjust for spatial autocorrelation and the small number problem. High-risk spatial clusters of DRMR were identified using Tango's flexible spatial scan statistics. Geographic distribution and high-risk mortality clusters were displayed using ArcGIS, whereas seasonal patterns were visually represented in Excel.

Results

A total of 54,684 deaths were reported during the study period. There was an increasing temporal trend as well as seasonal patterns in diabetes mortality risks with high risks occurring during the winter. The highest mortality risk (8.1 per 100,000 persons) was recorded during the winter of 2018, while the lowest (6.1 per 100,000 persons) was in the fall of 2010. County-level SEB smoothed mortality risks varied by geographic location, ranging from 12.6 to 81.1 deaths per 100,000 persons. Counties in the northern and central parts of the state tended to have high mortality risks, whereas southern counties consistently showed low mortality risks. Similar to the geographic distribution of DRMR, significant high-risk spatial clusters were also identified in the central and northern parts of Florida.

Conclusion

Geographic disparities of DRMR exist in Florida, with high-risk spatial clusters being observed in rural central and northern areas of the state. There is also evidence of both increasing temporal trends and Winter peaks of DRMR. These findings are helpful for guiding allocation of resources to control the disease, reduce disparities, and improve population health.

Geographic disparities and temporal changes of diabetes prevalence and diabetes self-management education program participation in Florida

BACKGROUND

Although Diabetes Self-Management Education (DSME) programs are recommended to help reduce the burden of diabetes and diabetes-related complications, Florida is one of the states with the lowest DSME participation rates. Moreover, there is evidence of geographic disparities of not only DSME participation rates but the burden of diabetes as well. Understanding these disparities is critical for guiding control programs geared at improving participation rates and diabetes outcomes. Therefore, the objectives of this study were to: (a) investigate geographic disparities of diabetes prevalence and DSME participation rates; and (b) identify predictors of the observed disparities in DSME participation rates.

METHODS

Behavioral Risk Factor Surveillance System (BRFSS) data for 2007 and 2010 were obtained from the Florida Department of Health. Age-adjusted diabetes prevalence and DSME participation rates were computed at the county level and their geographic distributions visualized using choropleth maps. Significant changes in diabetes prevalence and DSME participation rates between 2007 and 2010 were assessed and counties showing significant changes were mapped. Clusters of high diabetes prevalence before and after adjusting for common risk factors and DSME participation rates were identified, using Tango's flexible spatial scan statistics, and their geographic distribution displayed in maps. Determinants of the geographic distribution of DSME participation rates and predictors of the identified high rate clusters were identified using ordinary least squares and logistic regression models, respectively.

RESULTS

County level age-adjusted diabetes prevalence varied from 4.7% to 17.8% while DSME participation rates varied from 26.6% to 81.2%. There were significant (p≤0.05) increases in both overall age-adjusted diabetes prevalence and DSME participation rates from 2007 to 2010 with diabetes prevalence increasing from 7.7% in 2007 to 8.6% in 2010 while DSME participation rates increased from 51.4% in 2007 to 55.1% in 2010. Generally, DSME participation rates decreased in rural areas while they increased in urban areas. High prevalence clusters of diabetes (both adjusted and unadjusted) were identified in northern and central Florida, while clusters of high DSME participation rates were identified in central Florida. Rural counties and those with high proportion of Hispanics tended to have low DSME participation rates.

CONCLUSIONS

The findings confirm that geographic disparities in both diabetes prevalence and DSME participation rates exist. Specific attention is required to address these disparities especially in areas that have high diabetes prevalence but low DSME participation rates. Study findings are useful for guiding resource allocation geared at reducing disparities and improving diabetes outcomes.

Integration of Diabetes and Depression Care Is Associated with Glucose Control in Midwestern Federally Qualified Health Centers

BACKGROUND

The 2016 American Diabetes Association position statement emphasized that psychosocial and medical care should be integrated and provided to all people with diabetes.

OBJECTIVE

To determine whether better integration of diabetes and depression care is associated with better glycemic control.

DESIGN

Cross-sectional surveys of Midwestern federally qualified health center (FQHC) leaders and primary care providers (PCPs) in 2016. Responses were linked to FQHC-level data on the percentage of patients with uncontrolled diabetes (glycated hemoglobin ≥ 9%; 75 mmol/mol).

PARTICIPANTS

Midwest Clinicians' Network-affiliated FQHC leaders, and PCPs at the FQHCs.

MAIN MEASURES

Multilevel models were used to determine associations between the percentage of patients with uncontrolled diabetes and FQHC and PCP characteristics; presence of diabetes and behavioral health care services; and PCPs' perception of the stage of integration between diabetes and depression care services based on the transtheoretical model (i.e., pre-contemplation, contemplation, preparation, action, or maintenance).

KEY RESULTS

Response rates were 60% for the FQHC survey (N = 77) and 55% for the PCP survey (N = 538). In adjusted models, FQHCs in which PCPs perceived a higher stage of integration between diabetes and depression care had 3% fewer patients with uncontrolled diabetes per 1-level increase in integration stage (p = 0.01); on-site diabetes self-management education was associated with 7% fewer patients with uncontrolled diabetes (p < 0.01).

CONCLUSIONS

At Midwestern FQHCs, a higher stage of perceived integration of diabetes and depression care was associated with better FQHC-level glycemic control. Future studies are needed to elucidate what defines integration of diabetes and depression care services.