OBJECTIVE:Major successes in improving health in the United States during the past century have occurred as our nation moved through the epidemiologic transition from high infectious disease mortality to predominantly chronic disease mortality. The objective of this study was to identify successes in improving America's health in the first 2 decades of the 21st century. METHODS:We identified leading causes of death among US adults with age-adjusted mortality rates that declined by ≥20% from 2000 to 2019. RESULTS:Eleven disease categories achieved a ≥20% mortality reduction, including the leading causes of death in the United States (heart disease, stroke, cancer) and 2 infectious diseases. Seven of the 11 "success" conditions were forms of cancer, showing progress in screening, early diagnosis, treatment, and cure. A cautionary note is warranted for conditions with increasing cause-specific mortality, such as brain diseases, suicide, drug overdose, accidental deaths, and liver disease. CONCLUSIONS:The impact of research innovation translated into prevention and medical care is clearer with each passing decade. Similar strategies that prioritize behavioral health will be needed to reverse conditions with worsening mortality. Successful public health strategies have continued to reduce mortality from somatic "below-the-neck" causes, but parallel strategies are needed to address mental health, substance use, health behaviors, and healthy aging.

Background and Objectives: Mental health stigma remains prevalent in clinical practice, affecting even family physicians. Despite serving as frontline mental health providers, family physicians also face stigma and barriers to seeking care. Drawing on 2024 Council of Academic Family Medicine Educational Research Alliance study data, this study investigates family physician educators' perceptions of stigma, their help-seeking intentions, and the obstacles they encounter when pursuing mental health support. Methods: This cross-sectional study drew responses from a 2024 survey of family medicine educators and practicing physicians between October 15 and November 22, 2024. Out of the initial pool of 4,844 participants completing the survey, our sample included 1,195 respondents. One-way analysis of variance and simple linear regression were performed in Stata 14.0 to test our hypotheses rigorously. Results: Bivariate analyses identified statistically significant associations across five key relationships: years since degree completion and stigma score, age and stigma score, race and barriers to care, underrepresented in medicine status and barriers to care, and gender and barriers to care. Furthermore, linear regression models demonstrated that all three stigma categories (personal, perceived, and stigma of others) were significantly linked to higher barrier scores. Conclusions: These findings underscore the pervasive nature of mental health stigma among family physicians, highlighting its detrimental impact on helpseeking and well-being. Targeted interventions are crucial for reducing stigma, addressing barriers to care, and protecting physicians' mental health, ultimately improving patient outcomes.

Objective:This study was conducted to quantify the prevalence of metabolic syndrome and depressive symptoms across racial/ethnic and socioeconomic strata in a nationally representative U.S. sample. Methods:We used National Health and Nutrition Examination Survey 2017-March 2020 data for participants aged 18 years and older. Prevalence of depressive symptoms and metabolic syndrome alone and in combination was measured across racial/ethnic, sex, age, and income strata. Chi-square tests were used for between-group comparisons. Results:Over 7% of sampled adults had comorbid depressive symptoms and metabolic syndrome, representing 18.3 million Americans. These conditions were not equally distributed across racial/ethnic groups (χ2=124.28, P<.0001). The non-Hispanic Asian group was least likely to have either condition. Differences by economic status were also significant (χ2=86.61, P<.0001). Those in the highest economic group were least likely to have either or both conditions. Conclusions:Disparities in comorbid conditions exist across socioeconomic and demographic strata. Achieving optimal and equitable health outcomes for people with these comorbidities will require "whole-person-in-context" interventions. Integrated approaches to coexisting medical, psychological, and social complexities are needed.

Background Individuals with chronic physical conditions and comorbid mental illness have increased probability of adverse health outcomes. As minority populations have limited access to both medical care and culturally appropriate mental health services, having a comorbid mental health condition can further impede their ability to manage chronic conditions and widen racial disparities in health outcomes. Further, racial/ethnic disparities in treatment patterns are likely to exacerbate disparities in adverse health outcomes. Objective To identify the racial/ethnic mental health treatment patterns among individuals with cardiometabolic and depressive symptomology co-occurrence. Methods This study utilized National Health and Nutrition Examination Survey data, 2017 to March 2020 Pre-Pandemic. The primary analysis was an adjusted linear logistic regression analysis of race/ethnicity, comorbidity status and mental health treatment type. Regression models were estimated to determine the likelihood of receiving counseling and medication therapy, and to determine if the likelihood is associated with race/ethnicity. Results Primary findings indicate that depressive symptomology only was the most common designation and fewer than half of persons received any mental health treatment. Across all racial/ethnic groups, receiving no mental health treatment was the most common designation. Sixty-one percent of Non-Hispanic White persons and more than three out of four Hispanic and Non-Hispanic Black persons with only depressive symptoms received no mental health treatment. Adjusted regression analyses revealed that participants with comorbid cardiometabolic and depressive symptomology have 28% lower odds of receiving combined mental health professional and medication therapy than participants with depressive symptomology only. Conclusions Simultaneously treating both mental illness and cardiometabolic symptoms properly is complicated, but there may be untapped synergies in treating both concurrently. Therefore, to achieve favorable health outcomes, policy should be implemented to optimize clinical treatment by addressing aspects of both conditions in an integrated approach and may need to be culturally tailored to be effective.

Usual parametric and semi-parametric regression methods are inappropriate and inadequate for large clustered survival studies when the appropriate functional forms of the covariates and their interactions in hazard functions are unknown, and random cluster effects and cluster-level covariates are spatially correlated. We present a general nonparametric method for such studies under the Bayesian ensemble learning paradigm called Soft Bayesian Additive Regression Trees. Our methodological and computational challenges include large number of clusters, variable cluster sizes, and proper statistical augmentation of the unobservable cluster-level covariate using a data registry different from the main survival study. We use an innovative 3-step approach based on latent variables to address our computational challenges. We illustrate our method and its advantages over existing methods by assessing the impacts of intervention in some county-level and patient-level covariates to mitigate existing racial disparity in breast cancer survival in 67 Florida counties (clusters) using two different data resources. Florida Cancer Registry (FCR) is used to obtain clustered survival data with patient-level covariates, and the Behavioral Risk Factor Surveillance Survey (BRFSS) is used to obtain further data information on an unobservable county-level covariate of Screening Mammography Utilization (SMU).

Progress toward eliminating the Black-White disparity in US infant mortality rates has been slow and highly variable by state. Among thirty-two eligible states, eight had an increase (worsening), and twenty-four had a reduction (improvement) in their Black-White infant mortality rate ratios from 2008 to 2018. These findings necessitate dynamic, multilevel initiatives aimed at preventing Black infant deaths.

Purpose We built Bayesian Network (BN) models to explain roles of different patient-specific factors affecting racial differences in breast cancer stage at diagnosis, and to identify healthcare related factors that can be intervened to reduce racial health disparities. Methods We studied women age 67-74 with initial diagnosis of breast cancer during 2006-2014 in the National Cancer Institute's SEER-Medicare dataset. Our models included four measured variables (tumor grade, hormone receptor status, screening utilization and biopsy delay) expressed through two latent pathways-a tumor biology path, and health-care access/utilization path. We used various Bayesian model assessment tools to evaluate these two latent pathways as well as each of the four measured variables in explaining racial disparities in stage-at-diagnosis. Results Among 3,010 Black non-Hispanic (NH) and 30,310 White NH breast cancer patients, respectively 70.2% vs 76.9% were initially diagnosed at local stage, 25.3% vs 20.3% with regional stage, and 4.56% vs 2.80% with distant stage-at-diagnosis. Overall, BN performed approximately 4.7 times better than Classification And Regression Tree (CART) (Breiman L, Friedman JH, Stone CJ, Olshen RA. Classification and regression trees. CRC press; 1984) in predicting stage-at-diagnosis. The utilization of screening mammography is the most prominent contributor to the accuracy of the BN model. Hormone receptor (HR) status and tumor grade are useful for explaining racial disparity in stage-at diagnosis, while log-delay in biopsy impeded good prediction. Conclusions Mammography utilization had a significant effect on racial differences in breast cancer stage-at-diagnosis, while tumor biology factors had less impact. Biopsy delay also aided in predicting local and regional stages-at-diagnosis for Black NH women but not for white NH women.

Purpose: Staphylococcus aureus (S. aureus) remains a serious cause of infections in the United States and worldwide. In the United States, methicillin-resistant S. aureus (MRSA) is the leading cause of skin and soft tissue infections. This study identifies 'best' to 'worst' infection trends from 2002 to 2016, using group-based trajectory modeling approach. Methods: Electronic health records of children living in the southeastern United States with S. aureus infections from 2002 to 2016 were retrospectively studied, by applying a group-based trajectory model to estimate infection trends (low, high, very high), and then assess spatial significance of these trends at the census tract level; we focused on community-onset infections and not those considered healthcare acquired. Results: Three methicillin-susceptible S. aureus (MSSA) infection trends (low, high, very high) and three MRSA trends (low, high, very high) were identified from 2002 to 2016. Among census tracts with com-munity-onset S. aureus cases, 29% of tracts belonged to the best trend (low infection) for both methicillin-resistant S. aureus and methicillin-susceptible S. aureus; higher proportions occurring in the less densely populated areas. Race disparities were seen with the worst methicillin-resistant S. aureus infection trends and were more often in urban areas. Conclusions: Group-based trajectory modeling identified unique trends of S. aureus infection rates over time and space, giving insight into the associated population characteristics which reflect these trends of community-onset infection. (c) 2023 Published by Elsevier Inc.

Staphylococcus aureus (S. aureus) is known to cause human infections and since the late 1990s, community-onset antibiotic resistant infections (methicillin resistant S. aureus (MRSA)) continue to cause significant infections in the United States. Skin and soft tissue infections (SSTIs) still account for the majority of these in the outpatient setting. Machine learning can predict the location-based risks for community-level S. aureus infections. Multi-year (2002–2016) electronic health records of children <19 years old with S. aureus infections were queried for patient level data for demographic, clinical, and laboratory information. Area level data (Block group) was abstracted from U.S. Census data. A machine learning ecological niche model, maximum entropy (MaxEnt), was applied to assess model performance of specific place-based factors (determined a priori) associated with S. aureus infections; analyses were structured to compare methicillin resistant (MRSA) against methicillin sensitive S. aureus (MSSA) infections. Differences in rates of MRSA and MSSA infections were determined by comparing those which occurred in the early phase (2002–2005) and those in the later phase (2006–2016). Multi-level modeling was applied to identify risks factors for S. aureus infections. Among 16,124 unique patients with community-onset MRSA and MSSA, majority occurred in the most densely populated neighborhoods of Atlanta’s metropolitan area. MaxEnt model performance showed the training AUC ranged from 0.771 to 0.824, while the testing AUC ranged from 0.769 to 0.839. Population density was the area variable which contributed the most in predicting S. aureus disease (stratified by CO-MRSA and CO-MSSA) across early and late periods. Race contributed more to CO-MRSA prediction models during the early and late periods than for CO-MSSA. Machine learning accurately predicts which densely populated areas are at highest and lowest risk for community-onset S. aureus infections over a 14-year time span.

Background: Interpersonal primary care continuity or chronic condition continuity (CCC) is associated with improved health outcomes. Ambulatory care-sensitive conditions (ACSC) are best managed in a primary care setting, and chronic ACSC (CACSC) require management over time. However, current measures do not measure continuity for specific conditions or the impact of continuity for chronic conditions on health outcomes. The purpose of this study was to design a novel measure of CCC for CACSC in primary care and determine its association with health care utilization. Methods: We conducted a cross-sectional analysis of continuously enrolled, nondual eligible adult Medicaid enrollees with a diagnosis of a CACSC using 2009 Medicaid Analytic eXtract files from 26 states. We conducted adjusted and unadjusted logistic regression models of the relationship between patient continuity status and emergency department (ED) visits and hospitalizations. Models were adjusted for age, sex, race/ethnicity, comorbidity, and rurality. We defined CCC for CACSC as at least 2 outpatient visits with any primary care physician for a CACSC in the year, and (2) more than 50% of outpatient CACSC visits with a single PCP. Results: There were 2,674,587 enrollees with CACSC and 36.3% had CCC for CACSC visits. In fully adjusted models, enrollees with CCC were 28% less likely to have ED visits compared with those without CCC (aOR = 0.71, 95% CI = 0.71 - 0.72) and were 67% less likely to have hospitalization than those without CCC (aOR = 0.33, 95% CI = 0.32-0.33). Conclusions: CCC for CACSCs was associated with fewer ED visits and hospitalizations in a nationally representative sample of Medicaid enrollees. ( J Am Board Fam Med 2023;36:303-312.)

Purpose: To analyze the extent to which rural-urban differences in breast cancer stage at diagnosis are explained by factors including age, race, tumor grade, receptor status, and insurance status. Methods: Using the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) 18 database, analysis was performed using data from women aged 50-74 diagnosed with breast cancer between the years 2013 and 2016. Patient rurality of residence was coded according to SEER's Rural-Urban Continuum Code 2013: Large Urban (RUCC 1), Small Urban (RUCC 2,3), and Rural (RUCC 4,5,6,7,8,9). Stage at diagnosis was coded according to SEER's Combined Summary Stage 2000 (2004+) criteria: Localized (0,1), Regional (2,3,4,5), and Distant (7). Descriptive statistics were analyzed, and variations were tested for across rural-urban categories using Kruskall-Wallis and Kendall's tau-b tests. Additionally, odds ratios (ORs) and 95% confidence intervals for the three ordinal levels of rural-urban residence were calculated while adjusting for other independent variables using ordinal logistic regression. Results: The rural residence category showed the largest proportion of women diagnosed with distant stage breast cancer. Additionally, we determined that patients with residence in both large and small urban areas had statistically significantly lower odds of higher stage diagnosis compared to rural patients even after controlling for age, race, tumor grade, receptor status, and insurance status. Conclusions: Rural women with breast cancer show small but statistically significant disparities in stage-at-diagnosis. Further research is needed to understand local area variation in these disparities across a wide range of rural communities, and to identify the most effective interventions to eliminate these disparities.

Cancer incidence in the USA remains higher among certain groups, regions, and communities, and there are variations based on nativity. Research has primarily focused on specific groups and types of cancer. This study expands on previous studies to explore the relationship between country of birth (nativity) and all cancer site incidences among USA and foreign-born residents using a nationally representative sample. This is a cross-sectional study of (unweighted n = 22,554; weighted n = 231,175,933) participants between the ages of 20 and 80 from the National Health and Nutrition Examination Survey (NHANES) 2011–2018. Using weighted logistic regressions, we analyzed the impact of nativity on self-reported cancer diagnosis controlling for routine care, smoking status, overweight, race/ethnicity, age, and gender. We ran a partial model, adjusting only for age as a covariate, a full model with all other covariates, and stratified by race/ethnicity. In the partial and full models, our findings indicate that US-born individuals were more likely to report a cancer diagnosis compared to their foreign-born counterparts (OR 2.34, 95% CI [1.93; 2.84], p < 0.01) and (OR 1. 39, 95% CI [1.05; 1.84], p < 0.05), respectively. This significance persisted only among non-Hispanic Blacks when stratified by race. Non-Hispanic Blacks who were US-born were more likely to report a cancer diagnosis compared to their foreign-born counterparts (OR 2.30, 95% [CI 1.31; 4.02], p < 0.05). A variety of factors may reflect lower self-reported cancer diagnosis in foreign-born individuals in the USA other than a healthy immigrant advantage. Future studies should consider the factors behind the differences in cancer diagnoses based on nativity status, particularly among non-Hispanic Blacks.

Variation in breast cancer stage at initial diagnosis (including racial disparities) is driven both by tumor biology and healthcare factors. We studied women age 67–74 with initial diagnosis of breast cancer from 2006 through 2014 in the SEER-Medicare database. We extracted variables related to tumor biology (histologic grade and hormone receptor status) and healthcare factors (screening mammography [SM] utilization and time delay from mammography to diagnostic biopsy). We used naïve Bayesian networks (NBNs) to illustrate the relationships among patient-specific factors and stage-at-diagnosis for African American (AA) and white patients separately. After identifying and controlling confounders, we conducted counterfactual inference through the NBN, resulting in an unbiased evaluation of the causal effects of individual factors on the expected utility of stage-at-diagnosis. An NBN-based decomposition mechanism was developed to evaluate the contributions of each patient-specific factor to an actual racial disparity in stage-at-diagnosis. 2000 bootstrap samples from our training patients were used to compute the 95% confidence intervals (CIs) of these contributions. Using a causal-effect contribution analysis, the relative contributions of each patient-specific factor to the actual racial disparity in stage-at-diagnosis were as follows: tumor grade, 45.1% (95% CI: 44.5%, 45.8%); hormone receptor status, 5.0% (4.5%, 5.4%); mammography utilization, 23.1% (22.4%, 24.0%); and biopsy delay 26.8% (26.1%, 27.3%). The modifiable mechanisms of mammography utilization and biopsy delay drive about 49.9% of racial difference in stage-at-diagnosis, potentially guiding more targeted interventions to eliminate cancer outcome disparities.

Objective:Our goal was to explore prenatal practices and birthing experiences among Black women living in an urban North Florida community.Design:Non-random qualitative study.Setting:Private spaces at a convenient location selected by the participant.Participants:Eleven Black women, aged 25-36 years, who were either pregnant or had given birth at least once in the past five years in North Florida.Methods:Semi-structured interviews were completed in July 2017, followed by thematic analysis of interview transcripts.Results:Four main themes emerged: a) decision-making strategies for employing alternative childbirth preparation (ie, midwives, birthing centers, and doulas); b) having access to formal community resources to support their desired approaches to perinatal care; c) seeking advice from women with similar perspectives on birthing and parenting; and d) being confident in one's decisions. Despite seeking to incorporate "alternative" methods into their birthing plans, the majority of our participants ultimately delivered in-hospital.Conclusions:Preliminary results suggest that culturally relevant and patient-centered decision-making might enhance Black women's perinatal experience although further research is needed to see if these findings are generalizable to a heterogenous US Black population. Implications for childbirth educators and health care professionals include: 1) recognizing the importance of racially and professionally diverse staffing in obstetric care practices; 2) empowering patients to communicate and achieve their childbirth desires; 3) ensuring an environment that is not only free of discrimination and disrespect, but that embodies respect (as perceived by patients of varied racial backgrounds) and cultural competence; and, 4) providing access to education and care outside of traditional work hours.

BackgroundResearch on children and youth on the autism spectrum reveal racial and ethnic disparities in access to healthcare and utilization, but there is less research to understand how disparities persist as autistic adults age. We need to understand racial-ethnic inequities in obtaining eligibility for Medicare and/or Medicaid coverage, as well as inequities in spending for autistic enrollees under these public programs.MethodsWe conducted a cross-sectional cohort study of U.S. publicly-insured adults on the autism spectrum using 2012 Medicare-Medicaid Linked Enrollee Analytic Data Source (n = 172,071). We evaluated differences in race-ethnicity by eligibility (Medicare-only, Medicaid-only, Dual-Eligible) and spending.FindingsThe majority of white adults (49.87%) were full-dual eligible for both Medicare and Medicaid. In contrast, only 37.53% of Black, 34.65% Asian/Pacific Islander, and 35.94% of Hispanic beneficiaries were full-dual eligible for Medicare and Medicare, with most only eligible for state-funded Medicaid. Adjusted logistic models controlling for gender, intellectual disability status, costly chronic condition, rural status, county median income, and geographic region of residence revealed that Black beneficiaries were significantly less likely than white beneficiaries to be dual-eligible across all ages. Across these three beneficiary types, total spending exceeded $10 billion. Annual total expenditures median expenditures for full-dual and Medicaid-only eligible beneficiaries were higher among white beneficiaries as compared with Black beneficiaries.ConclusionsPublic health insurance in the U.S. including Medicare and Medicaid aim to reduce inequities in access to healthcare that might exist due to disability, income, or old age. In contrast to these ideals, our study reveals that racial-ethnic minority autistic adults who were eligible for public insurance across all U.S. states in 2012 experience disparities in eligibility for specific programs and spending. We call for further evaluation of system supports that promote clear pathways to disability and public health insurance among those with lifelong developmental disabilities.

Purpose : Cancer incidence in the US remains higher among certain groups, regions, and communities and there are variations based on nativity. Research has primarily focused on specific groups and types of cancer. This study expands on previous studies to explore the relationship between country of birth (nativity) and all cancer site incidences among US and foreign-born residents using a nationally representative sample. Methods : This is a cross-sectional study of (unweighted n= 22,554; weighted n =231,175,933) participants between the ages of 20 and 80 from the National Health and Nutrition Examination Survey (NHANES) 2011-2018. Using weighted logistic regressions, we analyzed the impact of nativity on self-reported cancer diagnosis controlling for routine care, smoking status, overweight, race/ethnicity, age, and gender. We ran a partial model, adjusting only for age as a covariate, and a full model with all other covariates. Results : In the partial and full models, our findings indicate that US-born individuals were more likely to report a cancer diagnosis compared to their foreign-born counterparts (OR = 2.34, 95% CI [1.93; 2.84], p<0.01), and (OR=1. 39, 95 % CI [1.05; 1.84], p < 0.05), respectively. There was a significant association between cancer diagnosis and routine care (OR=1.48, 95% [1.14; 1.93], p<0.01), overweight (OR=1.16, 95% CI [1.01; 1.34], p<0.05), and smoking status (OR=1.30, 95% CI [1.13; 1.49], p<0.01). Race/ethnicity, age and gender were also significantly associated with cancer diagnosis. Conclusion : A variety of factors may reflect lower cancer diagnosis in foreign-born individuals in the US other than a healthy immigrant advantage, including environmental factors.

Background After a certain age, cancer screening may expose older adults to unnecessary harms with limited benefits and represent inefficient use of health care resources. Objective To estimate the frequency of cervical, breast, and colorectal cancer screening among adults older than US Preventive Services Task Force (USPSTF) age thresholds at which screening is no longer considered routine and to identify physician and patient factors associated with low-value cancer screening. Design Observational study using pooled cross-sectional data (2011-2016) from the National Ambulatory Medical Care Survey, a nationally representative probability sample of US office-based physician visits. Participants Analyses for cervical and breast cancer screening were limited to visits by women over age 65 (N=37,818) and ages 75 and over (N=19,451), respectively. Analyses for colorectal cancer screening were limited to visits by patients over age 75 (N=31,543). Main Measures Cancer screening procedures were coded as low value using USPSTF age thresholds. Key Results Between 2011 and 2016, an estimated 509, 507, and 273 thousand potentially low-value Pap smears, mammograms, and colonoscopies/sigmoidoscopies, respectively, were ordered annually. Low-valuecervical cancer screening was less likely to occur for visits with older (vs. younger) patients. Compared to visits by non-HispanicWhite women, low-valuecervical and breast cancer screening was less likely to occur for visits by women whose race/ethnicitywas something other than non-HispanicWhite, non-HispanicBlack, or Hispanic. Obstetrician/gynecologistswere more likely to order low-valuePap smears and mammograms compared to family/generalpractice physicians. Conclusions Thousands of cervical, breast, and colorectal cancer screenings at ages beyond routine guideline thresholds occur each year in the USA. Further research is needed to understand whether this pattern represents clinical inertia and resistance to de-adoption of previous screening practices, or whether physicians and/or patients perceive a higher value in these tests than that endorsed by experts writing evidence-based guidelines.

Abstract Background Staphylococcus aureus (S. aureus) remains a serious cause of infections in the United States and worldwide. Methicillin susceptible S. aureus (MSSA) is the cause of half of all health care–associated staphylococcal infections, and Methicillin Resistant S. aureus (MRSA) is the leading cause of community onset skin and soft tissue infections in the US. This study looks at a 15-year trend of community onset (CO)-MRSA and MSSA infections and determines ‘best’ to ‘worst’ infection trends. We identified distinct groups of CO-MRSA and MSSA infection rate trajectories by grouping census tracts of the 20 county Atlanta Metropolitan Statistical Area (MSA) between 2002 to 2016 with similar temporal trajectories. Methods This is a retrospective study from 2002-2016, using electronic health records of children living in Atlanta, Georgia with S. aureus infections and relevant US census data (at the census tract level). A group based trajectory model was applied to generate community onset S. aureus trajectory infection groups (low, high, very high) by census tract and were mapped using ArcGIS. Results Three CO-MSSA infection groups (low, high, very high) and two CO-MRSA infection groups (low, high) were detected among 909 census tracts in the 20 counties. We found ~74% of all the census tracts with S.aureus occurrence during this time period belonged to low infection rate groups for both MRSA and MSSA, with a higher proportion occurring in the less densely populated counties. Census tracts in DeKalb County, one of Atlanta’s most densely populated areas, had the highest proportion of the worst infection trend patterns (CO-MRSA high or very high, CO-MSSA high or very high). Trends of Community-Onset MRSA and MSSA Infection Rates Based on Group-based Trajectory Models Spatial patterns for CO-MRSA and CO-MSSA Trajectory Trends in the Atlanta Metropolitan Area Between 2002 to 2016 Conclusion Trends of S. aureus infection patterns, stratified by antibiotic resistance over geographic areas and time, identify communities with higher risks for MRSA infection compared to MSSA infection. Further investigation of the determinants of the trajectory groupings and the geographic outliers identified by this study may be a way to target prevention strategies aimed to prevent S. aureus infections. Disclosures All Authors: No reported disclosures

Background Staphylococcus aureus ( S. aureus ) remains a serious cause of infections in the U.S. and worldwide. Non antibiotic resistant Staphylococcus aureus (methicillin susceptible or MSSA) is the cause of half of all health care–associated staphylococcal infections, and methicillin resistant Staphylococcus aureus (MRSA) still is the leading cause of community onset skin and soft tissue infections in the U.S. This is the first study to spatially look at trends of both community onset MRSA and MSSA infections over nine years and determine ‘best’ to ‘worst’ infection trends over a nine year period (2002-2010),which spanned when community onset MRSA infections were occurring in epidemic proportions across the U.S. Methods Retrospective study from 2002-2010, using electronic health records of children living in the southeastern U.S. (Atlanta, Georgia) with S. aureus infections and relevant U.S. census data (at the census tract level). The Proc Traj for SAS was applied to generate community onset MRSA and MSSA trajectory infection groups (low, high, very high, or deviant trends), and then, mapping of these trajectory groups using census tract boundaries. Results From community onset MRSA infection trend patterns (low, high, very high), only 0.8% of the census tracts showed a dramatic increase from 2002-2007 and then a gradual decline from 2008 to 2010. From community onset MSSA infection trend patterns (low and high), 85.7% of ‘high infection’ group persisted throughout the nine year period, compared to 14.3% of ‘low infection’ group over this same period. Low community onset MRSA and MSSA trend patterns were seen throughout the 20 counties of Atlanta, Georgia’s metropolitan statistical area, but more often seen in those counties less densley populated. Census tracts reflecting Atlanta’s ‘innercity’ had the highest proportion of the worst infection trend pattern (community onset MRSA-Very High-CO-MSSA-High or community onset MRSA-High-CO-MSSA-High). The deviant trend of community onset MRSA Very High- CO-MSSA Low infection were in census tracts east of downtown Atlanta. Conclusions ‘Trends’ of S. aureus infection patterns, stratified by antibiotic resistance, over geographic areas and time identify communities with higher risks for community onset MRSA infection compared to community onset MSSA infection.