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PurposeThe Population-based Microbiome Research Core (PMRC) is an expandable and longitudinal research core infrastructure to support the study of the human microbiome within the context of environmental, sociodemographic, and health factors. Broadly, the purpose of this infrastructure is to provide new insights into how human-environment interactions affect health through its influence on the composition and function of the microbiome. The PMRC was established as an ancillary study of the Survey of Health of Wisconsin (SHOW) and serves as a platform for ancillary studies, ongoing follow-up of the cohort, and expansion of the microbiome biorepository.ParticipantsThe study recruited adult participants who had previously participated in SHOW’s Wisconsin Microbiome Study (WMS). Over 59% of the eligible WMS participants agreed to provide a repeat stool sample and household samples including dust, high touch surface swabs and outside soil.Findings to datePMRC includes 323 individuals; the majority (96%) were over the age of eighteen, white (84%), urban (75%), and lived in their homes for over one year (92%). Overall, 97% of participants completed the questionnaire and household high-touch surface swab collection, and 93% and 94% completed dust and stool collection, respectively. Soil samples were collected for 86% of all participant homes.Future plansSample protocols developed for the PMRC offer a unique framework for future household-based microbiome research. This infrastructure can support the generation of new knowledge on the role of the home environment in relation to the human microbiome and identify new opportunities for intervention research.

Objective: To optimize type 1 diabetes (T1D) self-management, experts recommend tailoring care to meet people’s needs and preferences. To facilitate this tailoring, we developed and validated the Barriers and Supports Evaluation (BASES) tool to identify working-age adults’ T1D self-management barriers and supports. Methods: Participants were 25-64 year old adults with T1D recruited from clinics and a community-based registry. Guided by Social Cognitive Theory, content analysis of 33 semi-structured interviews was used to create a comprehensive item pool of 136 items, further refined to 70 candidate items on a 5-point Likert scale through cognitive interviewing and pilot testing. To develop and validate the tool, exploratory and confirmatory factor analyses were applied to 392 participants’ survey responses to the candidate barrier and support items. Additional survey data included demographics and the Diabetes-Specific Quality of Life Scale-Revised. To evaluate concurrent validity, A1c values from medical records and quality of life (QoL) scores were regressed on domain scores. Results: Factor analyses yielded 5 domains with a total of 30 items: (1) Cognitive Processes, (2) Costs and Insurance, (3) Learning Opportunities, (4) Family and Friend Support, and (5) Diabetes Provider Interactions. Models exhibited good to adequate fit, with Comparative Fit Index (CFI)>0.88 and Root Mean Squared Error of Approximation (RMSEA) Conclusions: The BASES tool is brief, patient-centered, and demonstrates construct and concurrent validity. The tool could be used in clinical practice to tailor diabetes support and education to individual’s needs, improving effectiveness of services. Disclosure E. D. Cox: None. E. M. Planalp: None. H. Kliems: None. M. Palta: n/a. T. J. Lecaire: None. B. A. Chewning: None. Funding American Diabetes Association (1-18-ICTS-026 to E.D.C.)

PurposeThe Survey of the Health of Wisconsin (SHOW) was established in 2008 by the University of Wisconsin (UW) School of Medicine and Public Health (SMPH) with the goals of 1) providing a timely and accurate picture of the health of the state residents; and 2) serving as an agile resource infrastructure for ancillary studies. Today SHOW continues to serve as a vital population health research infrastructure.ParticipantsSHOW currently includes 5,846 adult and 980 minor participants recruited between 2008-2019 in four primary waves. WAVE I (2008-2013) includes annual statewide representative samples of 3,380 adults ages 21 to 74 years. WAVE II (2014-2016) is a triannual statewide sample of 1957 adults (age ≥18 years) and 645 children. WAVE III (2017) consists of follow-up of 725 adults from the WAVE I and baseline surveys of 222 children in selected households. WAVEs II and III include stool samples collected as part of an ancillary study in a subset of 784 individuals. WAVE IV consist of 517 adults and 113 children recruited from traditionally under-represented populations in biomedical research including African Americans and Hispanics in Milwaukee county, WI.Findings to DateThe SHOW provides extensive data to examine the intersectionality of multiple social determinants and population health. SHOW includes a large biorepository and extensive health data collected in a geographically diverse urban and rural population. Over 60 studies have been published covering a broad range of topics including, urban and rural disparities in cardio-metabolic disease and cancer, objective physical activity, sleep, green-space and mental health, transcriptomics, the gut microbiome, antibiotic resistance, air pollution, concentrated animal feeding operations and heavy metal exposures.Future PlansThe SHOW cohort is available for continued longitudinal follow-up and ancillary studies including genetic, multi-omic and translational environmental health, aging, microbiome and COVID-19 research.Article SummaryStrengths and limitationsThe Survey of the Health of Wisconsin (SHOW) is an infrastructure to advance population health sciences including biological sample collection and broader data on individual and neighborhood social and environmental determinants of health.The extensive data from diverse urban and rural populations offers a unique study sample to compare how socio-economic gradients shape health outcomes in different contexts.The objective health data supports novel interdisciplinary research initiatives and is especially suited for research in causes and consequences of environmental exposures (physical, chemical, social) across the life course on cardiometabolic health, immunity, and aging related conditions.The extensive biorepository supports novel omics research into common biological mechanisms underlying numerous complex chronic conditions including inflammation, oxidative stress, metabolomics, and epigenetic modulation.Ancillary studies, such as the Wisconsin Microbiome Study, have expanded the utility of the study to examine human susceptibility to environmental exposures and opportunities for investigations of the role of microbiome in health and disease.Long-standing partnerships and recent participation among traditionally under-represented populations in biomedical research offer numerous opportunities to support community-driven health equity work.No biological samples were collected among children.The statewide sampling frame may limit generalizability to other regions in the United States.

Children’s sleep quality and duration are important to overall development, health, and wellbeing. However, measuring children’s sleep is challenging, especially in situations where objective assessment is impractical. This study aimed to assess age and proxy effects in comparing subjective sleep duration with objective measures, in a community-based sample of Wisconsin children (aged 6–17 years), recruited from 2014–2017. The sample participants had a mean age of 11.4 (standard deviation, 3.3) years and 52% of them were male. We used linear mixed effects models to test for age effects in proxy- and self-report groups separately, and a quasiexperimental regression discontinuity approach to compare subjective sleep duration with objective actigraphy estimates across proxy- and self-report groups. We found evidence of systematic overestimation of sleep duration when using subjective measurements but did not find evidence of age effects in either group. Based on these analyses, we found evidence of differential overestimation by proxy- or self-report condition. Proxy reporters overestimated sleep duration by 2.3 hours (95% confidence interval: 2.2, 2.4), compared with 1.0 hour (95% confidence interval: 0.7, 1.2) for self-reporters. These findings suggest that proxy- versus self-reporting conditions are an important consideration when designing a study, and that it might be beneficial to reduce the age at which children self-report.

Objectives This study aimed to understand the potential reach of continence promotion intervention formats among incontinent women. Methods The Survey of the Health of Wisconsin conducts household interviews on a population-based sample. In 2016, 399 adult women were asked about incontinence and likelihood of participation in continence promotion via 3 formats: single lecture, interactive 3-session workshop, or online. Descriptive analyses compared women likely versus unlikely to participate in continence promotion. To understand format preferences, modified grounded theory was used to conduct and analyze telephone interviews. Results One hundred eighty-seven (76%) of 246 incontinent women reported being likely to attend continence promotion: 111 (45%) for a single lecture, 43 (17%) for an interactive 3-session workshop, and 156 (64%) for an online program. Obesity, older age, nonwhite race, prior health program participation, and Internet use for health information were associated with reported continence promotion participation. Cited advantages of a single lecture included convenience and ability to ask questions. A workshop offered accountability, hands-on learning, and opportunity to learn from others; online format offered privacy, convenience, and self-directed learning. Conclusions Most incontinent women are willing to participate in continence promotion, especially online.

IntroductionTo optimize type 1 diabetes mellitus self-management, experts recommend a person-centered approach, in which care is tailored to meet people’s needs and preferences. Existing tools for tailoring type 1 diabetes mellitus education and support are limited by narrow focus, lack of strong association with meaningful outcomes like A1c, or having been developed before widespread use of modern diabetes technology. To facilitate comprehensive, effective tailoring for today’s working-aged adults with type 1 diabetes mellitus, we developed and validated the Barriers and Supports Evaluation (BASES).Research design and methodsParticipants 25–64 years of age with type 1 diabetes mellitus were recruited from clinics and a population-based registry. Content analysis of semistructured interviews (n=33) yielded a pool of 136 items, further refined to 70 candidate items on a 5-point Likert scale through cognitive interviewing and piloting. To develop and validate the tool, factor analyses were applied to responses to candidate items (n=392). Additional survey data included demographics and the Diabetes-Specific Quality of Life (QOL) Scale-Revised. To evaluate concurrent validity, hemoglobin A1c (HbA1c) values and QOL scores were regressed on domain scores.ResultsFactor analyses yielded 5 domains encompassing 30 items: Learning Opportunities, Costs and Insurance, Family and Friends, Coping and Behavioral Skills, and Diabetes Provider Interactions. Models exhibited good to adequate fit (Comparative Fit Index >0.88 and Root Mean Squared Error of Approximation ConclusionsThe BASES is a valid, comprehensive, person-centered tool that can tailor diabetes support and education to individuals’ needs in a modern practice environment, improving effectiveness and uptake of services. Clinicians could use the tool to uncover patient-specific barriers that limit success in achieving HbA1c goals and optimal QOL.

Background: Children attending daycare are at increased risk of carrying multidrug-resistant organisms (MDROs) compared to children not attending daycare. Carriage of MDROs greatly increases the risk of infection, not only in the child but also for others living in the household. Understanding the epidemiology of MDRO carriage in children is essential to devising effective containment strategies. Here, we present the findings from a cross-sectional study assessing MDRO carriage in daycare-attending and nonattending children in Wisconsin. Methods: We applied the following enrollment criteria: Children aged between 6 months and H. influenzae, S. pneumoniae, M. catarrhalis, and methicillin-resistant S. aureus (MRSA). Skin samples were cultured for MRSA, and stool samples were cultured for MRSA, C. difficile, vancomycin-resistant enterococci (VRE), and extended-spectrum β-lactamase–producing Gram-negative bacilli (ie, ESBL GNR). Results: In total, 44 children were enrolled in this study. The average age was 2.6 years and 50% were girls. Furthermore, 30 (68.2%) were identified by their parents as white, 9 (20.5%) as black, and 5 (11.3%) as other or multiracial. Incidentally, 23 children (52.3%) were enrolled in daycare. Overall, 18 children were positive for at least 1 organism, 9 of which had daycare exposure, and 5 children (1 in daycare) were positive for >1 organism (11.4%). From stool samples, 6 children (13.6%, 2 in daycare) were C. difficile carriers, 3 were VRE carriers (6.8%, 1 in daycare), 8 carried an ESBL GNR (18.2%, 4 in daycare), and 3 carried MRSA (6.8%, 1 in daycare). One child was positive for H. influenzae (2.3%, not in daycare) and 2 were positive for S. pneumoniae (4.6%, 1 in daycare) from nares swabs. One child was positive for MRSA (2.3%, not in daycare) from a skin swab. We detected no significant differences between children with and without daycare exposure for any organism. Conclusions: Children in this population had higher than expected rates of ESBL GNRs and MRSA for a community population. Daycare exposure was not correlated with increased carriage in this small pilot study, though larger longitudinal studies are needed.Funding: NoneDisclosures: None

BACKGROUND: Radon is the second leading cause of lung cancer in the U.S., the leading cause of lung cancer in nonsmokers, and is estimated to cause 21,000 deaths every year. Radon is especially prevalent in the upper Midwest. This study aimed to assess radon testing and mitigation practices among residential homeowners, landlords, and school districts in Wisconsin. METHODS: Two survey sample datasets were used to assess radon testing and mitigation in residential homes: the Survey of the Health of Wisconsin (SHOW) and Wisconsin Behavioral Risk Factor Surveillance System (BRFSS) survey. Wisconsin landlords and school administrators were surveyed to assess radon testing and mitigation in rental properties and schools, respectively. RESULTS: Approximately 30% of Wisconsin homeowners (22.1% from SHOW and 39.9% from BRFSS) have tested their properties for radon. Similarly, 31.0% of Wisconsin landlords (40/129) and 35.1% of Wisconsin school districts (78/222) have tested their schools for radon. Of homeowners with elevated radon, about 60% mitigated. School districts whose radon levels tested high most commonly did not mitigate, with costs and/or lack of funding cited as the most common barrier. DISCUSSION: Radon testing and mitigation practices are inadequate in Wisconsin, and future work will seek to determine the best methods to increase testing and mitigation and reduce radon-induced lung cancer deaths in Wisconsin.

Background/Aim: Obesity may increase human sensitivity to environmental toxicants through multiple mechanisms including inflammation. Obesity has been shown to increase susceptibility of asthma sym...

Background There is significant inappropriate and overuse of antibiotics in the United States. We describe patterns of self-reported actual use of antibiotics and indications in Wisconsin adults. Methods The Survey of the Health of Wisconsin (SHOW) is an annual health study of a wide range of health determinants and outcomes among a population-based sample of residents with targeted recruitment of underrepresented minorities. In 2016, SHOW initiated WARRIOR (Winning the War on Antibiotic Resistance), an ancillary study that assessed actual antibiotic use and indications among adults. Antibiotics were grouped by pharmacologic class, and indications were grouped into clinical categories. Descriptive statistics and logistic regression were used to examine factors associated with antibiotic use. Results Overall, 756 adults [435 female and 321 male; mean (SD) age=54.2 (16.5)] were recruited, and 256 (33.5%) reported antibiotic use in the past year. Females (OR=1.87, 95% CI: 1.29, 2.70), people with current comorbidities or history of certain health conditions (OR=2.04, 95% CI: 1.23, 3.39), and people with a mental health or developmental condition (OR=1.93, 95% CI: 1.33, 281) were statistically significantly more likely to report antibiotic use. BMI (kg/m2) was slightly higher among antibiotic users (31.2) than nonusers (29.8; P = 0.064). Diabetes, heavy drinking, and smoking history were not correlated with antibiotic use. Top antibiotic classes used were penicillins (31%), macrolides (12%), first-generation cephalosporins (9%), tetracyclines (8%), quinolones (7%), and nitroimidazoles (3%). Top indications reported were upper respiratory infection (URI; 32.3%), dental condition or procedure (21.0%), surgery (12.6%), lower respiratory infection (11%), urinary tract, bladder, or kidney infection (7%), skin or soft-tissue infection (6%), and insect bite or insect-borne infection (6%). Conclusion Antibiotic use varies among Wisconsin adults, and certain groups are more likely to have used antibiotics in the last year. The top two reported indications for antibiotics were categories with known high rates of inappropriate (e.g., URI) and prophylactic (i.e., dental) prescribing. Further studies are needed to determine specific opportunities to reduce antibiotic use in Wisconsin. Disclosures All authors: No reported disclosures.

Background The social and economic environment has become a major area of interest regarding the determinants of cardiovascular health. Among markers of economic distress, food insecurity has been found associated with metabolic disorders, dyslipidemia, and obesity, but no previous studies have examined its association with overall cardiovascular health. Methods and results We conducted a cross-sectional analysis among 2935 participants in the Survey of the Health of Wisconsin (SHOW), a statewide population-based representative sample. The presence of food insecurity was determined by an affirmative answer to the question “In the last 12 months, have you been concerned about having enough food for you or your family?” Cardiovascular health (CVH) was defined based on the American Heart Association Life's Simple 7 criteria and classified as “poor,” “intermediate,” or “ideal” using previously published criteria. “Good” CVH was defined as having no poor in any of the seven criteria (any amount of intermediate or ideal). Crude and adjusted odds ratios (OR) of good CVH according to presence of food insecurity were calculated using logistic regression models. Overall, food insecurity was associated with a decreased likelihood of good CVH (OR 0.53; 95% Confidence Interval 0.31 to 0.92; p = 0.02). This association persisted in models controlling for age, gender, race, and urbanization. Conclusions Participants who were food insecure were significantly less likely to have good CVH compared to participants who were food secure. Even though this study cannot confirm causality, these results suggest that food insecurity might be one of several socio-economic barriers contributing to poor CVH.

Background Our objective was to use a human factors and systems engineering approach to understand contributors to surgical readmissions from a patient and provider perspective. Previous studies on readmission have neglected the patient perspective. To address this gap and to better inform intervention design, we evaluated how transitions of care relate to and influence readmission from the patient and clinician perspective using the Systems Engineering Initiative for Patient Safety (SEIPS) model. Study design Patients readmitted within 30 days of discharge after complex abdominal surgery were interviewed. A focus group of inpatient clinician providers was conducted. Questions were guided by the SEIPS framework and content was analyzed. Data were collected concurrently from the medical record for a mixed-methods approach. Results Readmission occurred a median of 8 days (range 1 to 25 days) after discharge. All patients had follow-up scheduled with their surgeon, but readmission occurred before this in 72% of patients. Primary readmission diagnoses included infection, gastrointestinal complications, and dehydration. Patients (n = 18) and clinician providers (n = 6) identified a number of factors during the transition of care that may have contributed to readmission, including poor patient and caregiver understanding; inadequate discharge preparation for home care; insufficient educational process and materials, negatively affected by electronic health record design; and inadequate care team communication. Conclusions This is the first study to use a human factors and systems engineering approach to evaluate the impact of the quality of the transition of care and its influence on readmission from the patient and clinician perspective. Important targets for future interventions include enhancing the discharge process, improving education materials, and increasing care team coordination, with the overarching theme that improved patient and caregiver understanding and engagement are essential to decrease readmission and postdischarge health care use.