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Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data.

ABSTRACT: Geographic surveillance can identify hotspots of disease and reveal associations between health and the environment. Our study used emergency department surveillance to investigate geographic disparities in type 1 and type 2 diabetes prevalence among adults and children. Using all-payer emergency claims data from 2009 to 2013, we identified unique New York City residents with diabetes and geocoded their location using home addresses. Geospatial analysis was performed to estimate diabetes prevalence by New York City Census tract. We also used multivariable regression to identify neighborhood-level factors associated with higher diabetes prevalence. We estimated type 1 and type 2 diabetes prevalence at 0.23% and 10.5%, respectively, among adults and 0.20% and 0.11%, respectively, among children in New York City. Pediatric type 1 diabetes was associated with higher income (P = 0.001), whereas adult type 2 diabetes was associated with lower income (P < 0.001). Areas with a higher proportion of nearby restaurants categorized as fast food had a higher prevalence of all types of diabetes (P < 0.001) except for pediatric type 2 diabetes. Type 2 diabetes among children was only higher in neighborhoods with higher proportions of African American residents (P < 0.001). Our findings identify geographic disparities in diabetes prevalence that may require special attention to address the specific needs of adults and children living in these areas. Our results suggest that the food environment may be associated with higher type 1 diabetes prevalence. However, our analysis did not find a robust association with the food environment and pediatric type 2 diabetes, which was predominantly focused in African American neighborhoods.

SUBMITTER: Lee DC

PROVIDER: S-EPMC5920312 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data.

Lee David C DC Gallagher Mary Pat MP Gopalan Anjali A Osorio Marcela M Vinson Andrew J AJ Wall Stephen P SP Ravenell Joseph E JE Sevick Mary Ann MA Elbel Brian B

Journal of the Endocrine Society 20180417 5

Geographic surveillance can identify hotspots of disease and reveal associations between health and the environment. Our study used emergency department surveillance to investigate geographic disparities in type 1 and type 2 diabetes prevalence among adults and children. Using all-payer emergency claims data from 2009 to 2013, we identified unique New York City residents with diabetes and geocoded their location using home addresses. Geospatial analysis was performed to estimate diabetes prevale ...[more]

PMID: 29719877

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Project description:BackgroundAsthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.ObjectiveWe propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.MethodsWe performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.ResultsThere were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91-0.94) and 0.94 (0.93-0.96), respectively, for EMR and claims data, with positive predictive value of > 94%. The algorithms are visually presented using nomograms.ConclusionWe were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

Project description:BackgroundLeft unchecked, pre-diabetes progresses to diabetes and its complications that are important health burdens in the United States. There is evidence of geographic disparities in the condition with some areas having a significantly high risks of the condition and its risk factors. Identifying these disparities, their determinants, and changes in burden are useful for guiding control programs and stopping the progression of pre-diabetes to diabetes. Therefore, the objectives of this study were to investigate geographic disparities of pre-diabetes prevalence in Florida, identify predictors of the observed spatial patterns, as well as changes in disease burden between 2013 and 2016.MethodsThe 2013 and 2016 Behavioral Risk Factor Surveillance System data were obtained from the Florida Department of Health. Counties with significant changes in the prevalence of the condition between 2013 and 2016 were identified using tests for equality of proportions adjusted for multiple comparisons using the Simes method. Flexible scan statistics were used to identify significant high prevalence geographic clusters. Multivariable regression models were used to identify determinants of county-level pre-diabetes prevalence.ResultsThe state-wide age-adjusted prevalence of pre-diabetes increased significantly (p ≤ 0.05) from 8.0% in 2013 to 10.5% in 2016 with 72% (48/67) of the counties reporting statistically significant increases. Significant local geographic hotspots were identified. High prevalence of pre-diabetes tended to occur in counties with high proportions of non-Hispanic black population, low median household income, and low proportion of the population without health insurance coverage.ConclusionsGeographic disparities of pre-diabetes continues to exist in Florida with most counties reporting significant increases in prevalence between 2013 and 2016. These findings are critical for guiding health planning, resource allocation and intervention programs.

Project description:Background: There are substantial geographic disparities in the life expectancy (LE) across the U.S. with myocardial infarction (MI) contributing significantly to the differences between the states with highest (leading) and lowest (lagging) LE. This study aimed to systematically investigate the epidemiology of geographic disparities in MI among older adults. Methods: Data on MI outcomes among adults aged 65+ were derived from the Center for Disease Control and Prevention-sponsored Wide-Ranging Online Data for Epidemiologic Research database and a 5% sample of Medicare Beneficiaries for 2000-2017. Death certificate-based mortality from MI as underlying/multiple cause of death (CBM-UCD/CBM-MCD), incidence-based mortality (IBM), incidence, prevalence, prevalence at age 65, and 1-, 3-, and 5-year survival, and remaining LE at age 65 were estimated and compared between the leading and lagging states. Cox model was used to investigate the effect of residence in the lagging states on MI incidence and survival. Results: Between 2000 and 2017, MI mortality was higher in the lagging than in the leading states (per 100,000, CBM-UCD: 236.7-583.7 vs. 128.2-357.6, CBM-MCD: 322.7-707.7 vs. 182.4-437.7, IBM: 1330.5-1518.9 vs. 1003.3-1197.0). Compared to the leading states, lagging states had higher MI incidence (1.1-2.0% vs. 0.9-1.8%), prevalence (10.2-13.1% vs. 8.3-11.9%), pre-existing prevalence (2.5-5.1% vs. 1.4-3.6%), and lower survival (70.4 vs. 77.2% for 1-year, 63.2 vs. 67.2% for 3-year, and 52.1 vs. 58.7% for 5-year), and lower remaining LE at age 65 among MI patients (years, 8.8-10.9 vs. 9.9-12.8). Cox model results showed that the lagging states had greater risk of MI incidence [Adjusted hazards ratio, AHR (95% Confidence Interval, CI): 1.18 (1.16, 1.19)] and death after MI diagnosis [1.22 (1.21, 1.24)]. Study results also showed alarming declines in survival and remaining LE at age 65 among MI patients. Conclusion: There are substantial geographic disparities in MI outcomes, with lagging states having higher MI mortality, incidence, and prevalence, lower survival and remaining LE at age 65. Disparities in MI mortality in a great extent could be due to between-the-state differences in MI incidence, prevalence at age 65 and survival. Observed declines in survival and remaining LE require an urgent analysis of contributing factors that must be addressed.

Project description:ImportanceDiabetes is a severe metabolic disorder affecting human health worldwide, with increasing prevalence in low- and middle-income countries. Gaps in knowledge regarding factors that lead to diabetes and its association with tuberculosis (TB) endemicity at the national scale still exist, mainly because of the lack of large-scale dual testing and appropriate evaluation methods.ObjectivesTo identify locations in India where diabetes prevalence is concentrated, examine the association of diabetes with sociodemographic and behavioral covariates, and uncover where high regional TB endemicity overlaps with diabetes.Design, setting, and participantsThis cross-sectional study included 803 164 men aged 15 to 54 years and women aged 15 to 49 years who participated in the Demographic Health Survey (2015-2016), carried out by the India Ministry of Health and Family Welfare using a 2-stage clustered sampling, which included a diabetes estimation component. The survey was conducted from January 2015 to December 2016, and data analysis was conducted from July 2018 to January 2019.ExposuresSelf-reported diabetes status.Main outcomes and measuresSelf-reported diabetes status was used to estimate the association of covariates, including educational level, sex, age, religion, marital status, alcohol use, tobacco use, obesity status, and household socioeconomic level, with diabetes prevalence. Additionally, regional tuberculosis endemicity level, estimated using the India TB report for 2014 from the Revised National TB Program, was included to evaluate the national extent of the spatial overlap of diabetes and TB.ResultsAmong 803 164 sampled individuals (691 982 [86.2%] women; mean [SD] age, 30.09 [9.97] years), substantial geographic variation in diabetes prevalence in India was found, with a concentrated burden at the southern coastline (cluster 1, Andhra Pradesh and Telangana: prevalence, 3.01% [1864 of 61 948 individuals]; cluster 2, Tamil Nadup and Kerala: prevalence, 4.32% [3429 of 79 435 individuals]; cluster 3, east Orissa: prevalence, 2.81% [330 of 11 758 individuals]; cluster 4, Goa: prevalence, 4.43% [83 of 1883 individuals]). Having obesity and overweight (odds ratio [OR], 2.44; 95% CI, 2.18-2.73; P < .001; OR, 1.66; 95% CI, 1.52-1.82; P < .001, respectively), smoking tobacco (OR, 3.04; 95% CI, 1.66-5.56; P < .001), and consuming alcohol (OR, 2.01; 95% CI, 1.37-2.95; P < .001) were associated with increased odds of diabetes. Regional TB endemicity and diabetes spatial distributions showed that there is a lack of consistent geographical overlap between these 2 diseases (eg, TB cluster 4: 60 213 TB cases; 186.79 diabetes cases in 20 183.88 individuals; 0.93% diabetes prevalence; TB cluster 8: 47 381 TB cases; 180.53 diabetes cases in 22 449.18 individuals; 0.80% diabetes prevalence; TB cluster 9: 37 620 TB cases, 601.45 diabetes cases in 12 879.36 individuals; 4.67% diabetes prevalence).Conclusions and relevanceIn this study, identifying spatial clusters of diabetes on the basis of a nationally representative survey suggests that India may face different levels of disease severity, and each region might need to implement control strategies that are more appropriate for its unique epidemiologic context.

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Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data.

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Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data.

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