Background Community- associated methicillin resistant Staphylococcus aureus (CA-MRSA) cause serious infections and rates continue to rise worldwide. Use of geocoded electronic health record (EHR) data to prevent spread of disease is limited in health service research. We demonstrate how geocoded EHR and spatial analyses can be used to identify risks for CA-MRSA in children, which are tied to place-based determinants and would not be uncovered using traditional EHR data analyses. Methods An epidemiology study was conducted on children from January 1, 2002 through December 31, 2010 who were treated for Staphylococcus aureus infections. A generalized estimated equations (GEE) model was developed and crude and adjusted odds ratios were based on S. aureus risks. We measured the risk of S. aureus as standardized incidence ratios (SIR) calculated within aggregated US 2010 Census tracts called spatially adaptive filters, and then created maps that differentiate the geographic patterns of antibiotic resistant and non-resistant forms of S. aureus . Results CA-MRSA rates increased at higher rates compared to non-resistant forms, p = 0.01. Children with no or public health insurance had higher odds of CA-MRSA infection. Black children were almost 1.5 times as likely as white children to have CA-MRSA infections (aOR 95% CI 1.44,1.75, p < 0.0001); this finding persisted at the block group level ( p < 0.001) along with household crowding (p < 0.001). The youngest category of age (< 4 years) also had increased risk for CA-MRSA (aOR 1.65, 95%CI 1.48, 1.83, p < 0.0001). CA-MRSA encompasses larger areas with higher SIRs compared to non-resistant forms and were found in block groups with higher proportion of blacks ( r = 0.517, p < 0.001), younger age ( r = 0.137, p < 0.001), and crowding ( r = 0.320, p < 0.001). Conclusions In the Atlanta MSA, the risk for CA-MRSA is associated with neighborhood-level measures of racial composition, household crowding, and age of children. Neighborhoods which have higher proportion of blacks, household crowding, and children < 4 years of age are at greatest risk. Understanding spatial relationship at a community level and how it relates to risks for antibiotic resistant infections is important to combat the growing numbers and spread of such infections like CA-MRSA.

Background Despite evidence-based prevention and practice guidelines, asthma prevalence, treatment, and outcomes vary widely at individual and community levels. Asthma disproportionate/ly affects low-income and minority children, who comprise a large segment of the Medicaid population. Methods 2007 Medicaid claims data from 14 southern states was mapped for 556 counties to describe the local area variation in 1-year asthma prevalence rates, emergency department (ED) visit rates, and racial disparity rate ratios. Results One-year period prevalence of asthma ranged from 2.8% in Florida to 6.4% in Alabama, with a median prevalence rate of 4.1%. At the county level, the prevalence was higher for Black children and ranged from 1.03% in Manatee County, FL, to 21.0% in Hockley County, TX. Black–White rate ratios of prevalence ranged from 0.49 in LeFlore County, MS, to 3.87 in Flagler County, FL. Adjusted asthma ED visit rates ranged from 2.2 per 1000 children in Maryland to 16.5 in Alabama, with a median Black–White ED-visit rate ratio of 2.4. Rates were higher for Black children, ranging from 0.80 per 1000 in Wicomico County, MD, to 70 per 1000 in DeSoto County, FL. Rate ratios of ED visits ranged from 0.25 in Vernon Parish, LA, to 25.28 in Nelson County, KY. Conclusions and relevance Low-income children with Medicaid coverage still experience substantial variation in asthma prevalence and outcomes from one community to another. The pattern of worse outcomes for Black children also varies widely across counties. Eliminating this variation could substantially improve overall outcomes and eliminate asthma disparities.

Background:Antibiotic resistant bacteria like community-onset methicillin resistant Staphylococcus aureus (CO-MRSA) have continued to cause infections in children at alarming rates and are associated with health disparities. Geospatial analyses of individual and area level data can enhance disease surveillance and identify socio-demographic and geographic indicators to explain CO-MRSA disease transmission patterns and risks.Methods:A case control epidemiology approach was undertaken to compare children with CO-MRSA to a noninfectious condition (unintentional traumatic brain injury (uTBI)). In order to better understand the impact of place based risks in developing these types of infections, data from electronic health records (EHR) were obtained from CO-MRSA cases and compared to EHR data from controls (uTBI). US Census data was used to determine area level data. Multi-level statistical models were performed using risk factors determined a priori and geospatial analyses were conducted and mapped.Results:From 2002–2010, 4,613 with CO-MRSA and 34,758 with uTBI were seen from two pediatric hospitals in Atlanta, Georgia. Hispanic children had reduced odds of infection; females and public health insurance were more likely to have CO-MRSA. Spatial analyses indicate significant ‘hot spots’ for CO-MRSA and the overall spatial cluster locations, differed between CO-MRSA cases and uTBI controls.Conclusions:Differences exist in race, age, and type of health insurance between CO-MRSA cases compared to noninfectious control group. Geographic clustering of cases is distinct from controls, suggesting placed based factors impact risk for CO-MRSA infection.

Background U.S. breast cancer deaths have been declining since 1989, but African American women are still more likely than white women to die of breast cancer. Black-white disparities in breast cancer mortality rate-ratios have actually been increasing. Methods Across 762 U.S. counties with enough deaths to generate reliable rates, we examined county-level age-adjusted breast cancer mortality rates for women aged 35–74 during the period 1989–2010. Twenty-two years of mortality data generated 20 three-year rolling average data points, each centered on a specific year from 1990 – 2009. We used mixed linear models to group each county into one of four mutually exclusive trend patterns. We also categorized the most recent three-year average black breast cancer mortality rate for each county as being worse than or not worse than the breast cancer mortality rate for the total U.S. population. Results More than half of counties (54%) showed persistent, unchanging disparities. Roughly one in four (24%) had a divergent pattern of worsening black-white disparities. However, 10.5% of counties sustained racial equality over the 20-year period, and 11.7% of counties actually showed a converging pattern from high disparities to greater equality. Twenty-three counties had 2008–2010 black mortality rates better than the U.S. average mortality rate. Conclusion Disparities are not inevitable. Four U.S. counties have sustained both optimal and equitable black outcomes, as measured by both absolute (better than US average) and relative (equality in local black-white rate-ratio) benchmarks for decades, while six counties have shown a path from disparities to health equity.