Income and rural-urban status moderate the association between income inequality and life expectancy in US census tracts.

BACKGROUND: A preponderance of evidence suggests that higher income inequality is associated with poorer population health, yet recent research suggests that this association may vary based on other social determinants, such as socioeconomic status (SES) and other geographic factors, such as rural-urban status. The objective of this empirical study was to assess the potential for SES and rural-urban status to moderate the association between income inequality and life expectancy (LE) at the census-tract level. METHODS: Census-tract LE values for 2010-2015 were abstracted from the US Small-area Life Expectancy Estimates Project and linked by census tract to Gini index, a summary measure of income inequality, median household income, and population density for all US census tracts with non-zero populations (n = 66,857). Partial correlation and multivariable linear regression modeling was used to examine the association between Gini index and LE using stratification by median household income and interaction terms to assess statistical significance. RESULTS: In the four lowest quintiles of income in the four most rural quintiles of census tracts, the associations between LE and Gini index were significant and negative (p between < 0.001 and 0.021). In contrast, the associations between LE and Gini index were significant and positive for the census tracts in the highest income quintiles, regardless of rural-urban status. CONCLUSION: The magnitude and direction of the association between income inequality and population health depend upon area-level income and, to a lesser extent, on rural-urban status. The rationale behind these unexpected findings remains unclear. Further research is needed to understand the mechanisms driving these patterns.

Black/White Disparities in Obesity Widen with Increasing Rurality: Evidence from a National Survey.

Background: Racial health disparities in obesity and obesity-related conditions and behaviors are well documented, although a small body of research suggests that geographic factors (e.g., socioeconomic status [SES] and rural/urban status) may alter the magnitude of these disparities. Methods: This study explored how rurality moderates black/white health disparities using a nationally representative sample from the 2012 Behavioral Risk Factor Surveillance System (n=359,157). Respondents' county of residence was linked to the U.S. Census information to obtain the county-level Index of Relative Rurality (IRR). Weighted logistic regression was used to model obesity, diabetes, and lack of physical activity (PA) on race (black/white), IRR, and an interaction term of race and IRR, including covariates (age, sex, education, marital status, employment, and income). Results: Blacks were significantly more likely to have obesity, diabetes, and a lack of PA compared with whites. Irrespective of race, rural respondents were significantly more likely to have obesity (odds ratio [OR] 1.035, confidence interval [95% CI] 1.028-1.043) and a lack of PA (OR 1.045, 95% CI 1.038-1.053) than respondents in more urban areas. For obesity and diabetes, the interaction term for black×IRR quintile was significant and positive, indicating an increase in the magnitude of the black/white disparity with increasing rurality. Discussion: These findings underscore the need for policies and programs aimed to reduce racial disparities in obesity and related conditions to consider the geographic context in which these outcomes occur.

The Economic Burden of Elevated Blood Glucose Levels in 2017: Diagnosed and Undiagnosed Diabetes, Gestational Diabetes Mellitus, and Prediabetes.

OBJECTIVE: This study was conducted to update national estimates of the economic burden of undiagnosed diabetes, prediabetes, and gestational diabetes mellitus (GDM) in the United States for year 2017 and provide state-level estimates. Combined with published estimates for diagnosed diabetes, these updated statistics provide a detailed picture of the economic costs associated with elevated blood glucose levels. RESEARCH DESIGN AND METHODS: This study estimated medical expenditures exceeding levels occurring in the absence of diabetes or prediabetes and the indirect economic burden associated with reduced labor force participation and productivity. Data sources analyzed included Optum medical claims for ∼5.8 million commercially insured patients continuously enrolled from 2013 to 2015, Medicare Standard Analytical Files containing medical claims for ∼2.8 million Medicare patients in 2014, and the 2014 Nationwide Inpatient Sample containing ∼7.1 million discharge records. Other data sources were the U.S. Census Bureau, Centers for Disease Control and Prevention, and Centers for Medicare & Medicaid Services. RESULTS: The economic burden associated with diagnosed diabetes (all ages), undiagnosed diabetes and prediabetes (adults), and GDM (mothers and newborns) reached nearly $404 billion in 2017, consisting of $327.2 billion for diagnosed diabetes, $31.7 billion for undiagnosed diabetes, $43.4 billion for prediabetes, and nearly $1.6 billion for GDM. Combined, this amounted to an economic burden of $1,240 for each American in 2017. Annual burden per case averaged $13,240 for diagnosed diabetes, $5,800 for GDM, $4,250 for undiagnosed diabetes, and $500 for prediabetes. CONCLUSIONS: Updated statistics underscore the importance of reducing the burden of prediabetes and diabetes through better detection, prevention, and treatment.

Diabetes diagnosis and management among insured adults across metropolitan areas in the U.S.

This study provides diabetes-related metrics for the 50 largest metropolitan areas in the U.S. in 2012-including prevalence of diagnosed and undiagnosed diabetes, insurance status of the population with diabetes, diabetes medication use, and prevalence of poorly controlled diabetes. Diabetes prevalence estimates were calculated using cross-sectional data combining the Behavioral Risk Factor Surveillance System, American Community Survey, National Nursing Home Survey, Census population files, and National Health and Nutrition Examination Survey. Analysis of medical claims files (2012 de-identified Normative Health Information database, 2011 Medicare Standard Analytical Files, and 2008 Medicaid Analytic eXtract) produced information on treatment and poorly controlled diabetes by geographic location, insurance type, sex, and age group. Among insured adults with diagnosed type 2 diabetes in 2012, the proportion receiving diabetes medications ranged from 83% in Oklahoma City, Oklahoma, to 65% in West Palm Beach, Florida. The proportion of treated patients with medical claims indicating poorly controlled diabetes was lowest in Minneapolis, Minnesota (36%) and highest in Texas metropolitan areas of Austin (51%), San Antonio (51%), and Houston (50%). Estimates of diabetes detection and management across metropolitan areas often differ from state and national estimates. Local metrics of diabetes management can be helpful for tracking improvements in communities over time.

Diabetes 2030: Insights from Yesterday, Today, and Future Trends.

To forecast future trends in diabetes prevalence, morbidity, and costs in the United States, the Institute for Alternative Futures has updated its diabetes forecasting model and extended its projections to 2030 for the nation, all states, and several metropolitan areas. This paper describes the methodology and data sources for these diabetes forecasts and discusses key implications. In short, diabetes will remain a major health crisis in America, in spite of medical advances and prevention efforts. The prevalence of diabetes (type 2 diabetes and type 1 diabetes) will increase by 54% to more than 54.9 million Americans between 2015 and 2030; annual deaths attributed to diabetes will climb by 38% to 385,800; and total annual medical and societal costs related to diabetes will increase 53% to more than $622 billion by 2030. Improvements in management reducing the annual incidence of morbidities and premature deaths related to diabetes over this time period will result in diabetes patients living longer, but requiring many years of comprehensive management of multiple chronic diseases, resulting in dramatically increased costs. Aggressive population health measures, including increased availability of diabetes prevention programs, could help millions of adults prevent or delay the progression to type 2 diabetes, thereby helping turn around these dire projections.

Type 2 diabetes detection and management among insured adults.

BACKGROUND: The Centers for Disease Control and Prevention estimates that 28.9 million adults had diabetes in 2012 in the US, though many patients are undiagnosed or not managing their condition. This study provides US national and state estimates of insured adults with type 2 diabetes who are diagnosed, receiving exams and medication, managing glycemic levels, with diabetes complications, and their health expenditures. Such information can be used for benchmarking and to identify gaps in diabetes detection and management. METHODS: The study combines analysis of survey data with medical claims analysis for the commercially insured, Medicare, and Medicaid populations to estimate the number of adults with diagnosed type 2 diabetes and undiagnosed diabetes by insurance type, age, and sex. Medical claims analysis used the 2012 de-identified Normative Health Information database covering a nationally representative commercially insured population, the 2011 Medicare 5% Sample, and the 2008 Medicaid Mini-Max. RESULTS: Among insured adults in 2012, approximately 16.9 million had diagnosed type 2 diabetes, 1.45 million had diagnosed type 1 diabetes, and 6.9 million had undiagnosed diabetes. Of those with diagnosed type 2, approximately 13.0 million (77%) received diabetes medication-ranging from 70% in New Jersey to 82% in Utah. Suboptimal percentages had claims indicating recommended exams were performed. Of those receiving diabetes medication, 43% (5.6 million) had medical claims indicating poorly controlled diabetes-ranging from 29% with poor control in Minnesota and Iowa to 53% in Texas. Poor control was correlated with higher prevalence of neurological complications (+14%), renal complications (+14%), and peripheral vascular disease (+11%). Patients with poor control averaged $4,860 higher average annual health care expenditures-ranging from $6,680 for commercially insured patients to $4,360 for Medicaid and $3,430 for Medicare patients. CONCLUSIONS: This study highlights the large number of insured adults with undiagnosed type 2 diabetes by insurance type and state. Furthermore, this study sheds light on other gaps in diabetes care quality among patients with diagnosed diabetes and corresponding poorly controlled diabetes. These findings underscore the need for improvements in data collection and diabetes screening and management, along with policies that support these improvements.

An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations.

We investigate the inverse problem of identifying a conditional probability measure in measure-dependent evolution equations arising in size-structured population modeling. We formulate the inverse problem as a least squares problem for the probability measure estimation. Using the Prohorov metric framework, we prove existence and consistency of the least squares estimates and outline a discretization scheme for approximating a conditional probability measure. For this scheme, we prove general method stability. The work is motivated by Partial Differential Equation (PDE) models of flocculation for which the shape of the post-fragmentation conditional probability measure greatly impacts the solution dynamics. To illustrate our methodology, we apply the theory to a particular PDE model that arises in the study of population dynamics for flocculating bacterial aggregates in suspension, and provide numerical evidence for the utility of the approach.

Postfragmentation density function for bacterial aggregates in laminar flow.

The postfragmentation probability density of daughter flocs is one of the least well-understood aspects of modeling flocculation. We use three-dimensional positional data of Klebsiella pneumoniae bacterial flocs in suspension and the knowledge of hydrodynamic properties of a laminar flow field to construct a probability density function of floc volumes after a fragmentation event. We provide computational results which predict that the primary fragmentation mechanism for large flocs is erosion. The postfragmentation probability density function has a strong dependence on the size of the original floc and indicates that most fragmentation events result in clumps of one to three bacteria eroding from the original floc. We also provide numerical evidence that exhaustive fragmentation yields a limiting density inconsistent with the log-normal density predicted in the literature, most likely due to the heterogeneous nature of K. pneumoniae flocs. To support our conclusions, artificial flocs were generated and display similar postfragmentation density and exhaustive fragmentation.

Bilateral ocular hypertension with rapidly progressive optic neuropathy in a teen.

PURPOSE: We report a rare case of bilateral juvenile open-angle glaucoma (JOAG), with discussion of current understanding of its pathogenesis, differential diagnosis, genetics, and management. The importance of tonometry and dilated fundus examination as essential parts of a complete ocular examination, regardless of patient age, is emphasized. CASE REPORT: A Hispanic female teenager presented for an updated eye examination as a requirement before joining military boot camp. Chief concern was blurry vision at distance, with no other reported ocular or systemic problems. She manifested simple myopia in both eyes and was correctable to 20/20 in each eye with glasses. However, intraocular pressure (IOP) in each eye was measured above 40 mm Hg. Subsequent automated perimetry showed significant visual field defects, and laser polarimetry analysis of the optic nerve fibers corresponded with the visual field loss pattern. Maximal medical therapy was administered to lower the IOP, with minimal success. Subsequent incisional trabeculectomy with topical antimetabolite were performed in both eyes to achieve adequate control of her IOPs. CONCLUSIONS: Juvenile-onset Open Angle Glaucoma (JOAG) has been proposed to be a small subset of Primary Open Angle Glaucoma (POAG) and on a continual spectrum of Primary Open Angle Glaucoma. Because most patients with JOAG are asymptomatic, tonometry and optic nerve analysis are crucial in early detection and, thus, must be performed on all patients, young and old. JOAG has a variable onset, with rapidly progressive neuropathy that does not respond well to medical therapy alone, and surgical intervention is often the eventual treatment of choice. Mutations in the myocillin gene have been strongly linked to the disease. JOAG follows an autosomal dominant inheritance with relatively high penetrance. As such, close monitoring, genetics screening, and/or early medical management to prevent irreversible optic neuropathy and blindness should be considered as well for presymptomatic family members.