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OBJECTIVES: We examined whether the geographic density of alcohol retailers was greater in geographic areas with higher levels of demographic characteristics that predict health disparities. METHODS: We obtained the locations of all alcohol retailers in the continental United States and created a map depicting alcohol retail outlet density at the US Census tract level. US Census data provided tract-level measures of poverty, education, crowding, and race/ethnicity. We used multiple linear regression to assess relationships between these variables and retail alcohol density. RESULTS: In urban areas, retail alcohol density had significant nonlinear relationships with Black race, Latino ethnicity, poverty, and education, with slopes increasing substantially throughout the highest quartile for each predictor. In high-proportion Latino communities, retail alcohol density was twice as high as the median density. Retail alcohol density had little or no relationship with the demographic factors of interest in suburban, large town, or rural census tracts. CONCLUSIONS: Greater density of alcohol retailers was associated with higher levels of poverty and with higher proportions of Blacks and Latinos in urban census tracts. These disparities could contribute to higher morbidity in these geographic areas. [ABSTRACT FROM AUTHOR]

Topical fluoroquinolones are now available for use in the eye and ear. Their broad spectrum of activity includes the common eye and ear pathogens Staphylococcus aureus and Pseudomonas aeruginosa. For the treatment of acute otitis externa, these agents are as effective as previously available otic preparations. For the treatment of otitis media with tympanic membrane perforation, topical fluoroquinolones are effective and safe. These preparations are approved for use in children, and lack of ototoxicity permits prolonged administration when necessary. Topical fluoroquinolones are not appropriate for the treatment of uncomplicated conjunctivitis where narrower spectrum agents suffice; they represent a simplified regimen for the treatment of bacterial keratitis (corneal ulcers). When administered topically, fluoroquinolones are well tolerated and offer convenient dosing schedules. Currently, bacterial resistance appears limited. [ABSTRACT FROM AUTHOR]

Obesity is one of the most common medical problems in the United States and a risk factor for illnesses such as hypertension, diabetes, degenerative arthritis and myocardial infarction. It is a cause of significant morbidity and mortality and generates great social and financial costs. Obesity is defined as a body mass index greater than 30. Many patients accomplish weight loss with diet, exercise and lifestyle modification. Others require more aggressive therapy. Weight loss medications may be appropriate for use in selected patients who meet the definition of obesity or who are overweight with comorbid conditions. Medications are formulated to reduce energy intake, increase energy output or decrease the absorption of nutrients. Drugs cannot replace diet, exercise and lifestyle modification, which remain the cornerstones of obesity treatment. Two new agents, sibutramine and orlistat, exhibit novel mechanisms of action and avoid some of the side effects that occurred with earlier drugs. Sibutramine acts to block uptake of serotonin, norepinephrine and dopamine, while orlistat decreases fat absorption in the intestines. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Early detection of breast cancer by screening mammography aims to increase treatment options and decrease mortality. Recent studies have shown inconsistent results in their investigations of the possible association between travel distance to mammography and stage of breast cancer at diagnosis. OBJECTIVE: The purpose of the study was to investigate whether geographic access to mammography screening is associated with the stage at breast cancer diagnosis. METHODS: Using the state's population-based cancer registry, all female residents of New Hampshire aged > or =40 years who were diagnosed with breast cancer during 1998-2004 were identified. The factors associated with early stage (stages 0 to 2) or later stage (stages 3 and 4) diagnosis of breast cancer were compared, with emphasis on the distance a woman lived from the closest mammography screening facility, and residence in rural and urban locations. RESULTS: A total of 5966 New Hampshire women were diagnosed with breast cancer during 1998-2004. Their mean driving distance to the nearest mammography facility was 8.85 km (range 0-44.26; 5.5 miles, range 0-27.5), with a mean estimated travel time of 8.9 min (range 0.0-42.2). The distribution of travel distance (and travel time) was substantially skewed to the right: 56% of patients lived within 8 km (5 miles) of a mammography facility, and 65% had a travel time of less than 10 min. There was no significant association between later stage of breast cancer and travel time to the nearest mammography facility. Using 3 categories of rural/urban residence based on Rural Urban Commuting Area classification, no significant association between rural residence and stage of diagnosis was found. New Hampshire women were more likely to be diagnosed with breast cancer at later stages if they lacked private health insurance (p<0.001), were not married (p<0.001), were older (p<0.001), and there was a borderline association with diagnosis during non-winter months (p=0.074). CONCLUSIONS: Most women living in New Hampshire have good geographical access to mammography, and no indication was found that travel time or travel distance to mammography significantly affected stage at breast cancer diagnosis. Health insurance, age and marital status were the major factors associated with later stage breast cancer. The study contributes to an ongoing debate over geographic access to screening mammography in different states, which have given contradictory results. These inconsistencies in the rural health literature highlight a need to understand the complexity of defining rural and urban residence; to characterize more precisely the issues that contribute to good preventive care in different rural communities; and to appreciate the efforts already made in some rural states to provide good geographic access to preventive care. In New Hampshire, specific subgroups such as the uninsured and the elderly remain at greatest risk of being diagnosed with later stage breast cancer and may benefit from targeted interventions to improve early detection. [ABSTRACT FROM AUTHOR]

Background: Symptomatic COVID-19 and Long COVID, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or post-COVID conditions, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We sought to estimate the prevalence of reported COVID-19, symptomatic COVID-19, and Long COVID in college athletes in the United States attending 18 schools from spring 2020 to fall 2021., Methods: We developed an online survey to measure the prevalence of student athletes who tested positive for COVID-19, developed Long COVID, and did not return to their sport during the relevant time period. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. Of those schools surveyed, 16 responded regarding the spring 2020 semester, and 18 responded regarding the full academic year of fall 2020 to spring 2021 (both semesters)., Results: According to the survey responses, there were 9.8% of student athletes who tested positive for COVID-19 in spring 2020 and 25.4% who tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection., Conclusions: This study highlights that Long COVID occurs among young, healthy athletes and is a real consequence of COVID-19. Understanding the prevalence of Long COVID in this population requires longer follow-up and further study., (© 2023. The Author(s).)

VISUAL ABSTRACT ., (© 2022 Annals of Family Medicine, Inc.)

The COVID-19 pandemic prompted widespread closures of primary and secondary schools. Routine testing of asymptomatic students and staff members, as part of a comprehensive mitigation program, can help schools open safely. "Pooling in a pod" is a public health surveillance strategy whereby testing cohorts (pods) are based on social relationships and physical proximity. Pooled testing provides a single laboratory test result for the entire pod, rather than a separate result for each person in the pod. During the 2020-2021 school year, an independent preschool-grade 12 school in Washington, DC, used pooling in a pod for weekly on-site point-of-care testing of all staff members and students. Staff members and older students self-collected anterior nares samples, and trained staff members collected samples from younger students. Overall, 12 885 samples were tested in 1737 pools for 863 students and 264 staff members from November 30, 2020, through April 30, 2021. The average pool size was 7.4 people. The average time from sample collection to pool test result was 40 minutes. The direct testing cost per person per week was $24.24, including swabs. During the study period, 4 surveillance test pools received positive test results for COVID-19. A post-launch survey found most parents (90.3%), students (93.4%), and staff members (98.8%) were willing to participate in pooled testing with confirmatory tests for pool members who received a positive test result. The proportion of students in remote learning decreased by 62.2% for students in grades 6-12 ( P < .001) and by 92.4% for students in preschool to grade 5 after program initiation ( P < .001). Pooling in a pod is a feasible, cost-effective surveillance strategy that may facilitate safe, sustainable, in-person schooling during a pandemic.

Background: The negative impact of continued school closures during the height of the COVID-19 pandemic warrants the establishment of cost-effective strategies for surveillance and screening to safely reopen and monitor for potential in-school transmission. Here, we present a novel approach to increase the availability of repetitive and routine COVID-19 testing that may ultimately reduce the overall viral burden in the community., Methods: We implemented a testing program using the SalivaClear࣪ pooled surveillance method that included students, faculty and staff from K-12 schools (student age range 5-18 years) and universities (student age range >18 years) across the country (Mirimus Clinical Labs, Brooklyn, NY). The data analysis was performed using descriptive statistics, kappa agreement, and outlier detection analysis., Findings: From August 27, 2020 until January 13, 2021, 253,406 saliva specimens were self-collected from students, faculty and staff from 93 K-12 schools and 18 universities. Pool sizes of up to 24 samples were tested over a 20-week period. Pooled testing did not significantly alter the sensitivity of the molecular assay in terms of both qualitative (100% detection rate on both pooled and individual samples) and quantitative (comparable cycle threshold (Ct) values between pooled and individual samples) measures. The detection of SARS-CoV-2 in saliva was comparable to the nasopharyngeal swab. Pooling samples substantially reduced the costs associated with PCR testing and allowed schools to rapidly assess transmission and adjust prevention protocols as necessary. In one instance, in-school transmission of the virus was determined within the main office and led to review and revision of heating, ventilating and air-conditioning systems., Interpretation: By establishing low-cost, weekly testing of students and faculty, pooled saliva analysis for the presence of SARS-CoV-2 enabled schools to determine whether transmission had occurred, make data-driven decisions, and adjust safety protocols. We provide strong evidence that pooled testing may be a fundamental component to the reopening of schools by minimizing the risk of in-school transmission among students and faculty., Funding: Skoll Foundation generously provided funding to Mobilizing Foundation and Mirimus for these studies., Competing Interests: None., (© 2021 The Author(s).)

Introduction: Walking has the potential to promote health across the life span, but age-specific features of the neighborhood environment (NE), especially in rural communities, linked with walking have not been adequately characterized. This study examines the relationships between NE and utilitarian walking among older vs. younger adults living in US rural towns. Methods: Data for this cross-sectional study came from telephone interviews in 2011-2012 with 2,140 randomly sampled younger (18-64 years, n = 1,398) and older (65+ years, n = 742) adults, collecting personal and NE perception variables. NE around each participant's home was also measured objectively using geographic information system techniques. Separate mixed-effects logistic regression models were estimated for the two age groups, predicting the odds of utilitarian walking at least once a week. Results: Perceived presence of crosswalks and pedestrian signals was significantly related to utilitarian walking in both age groups. Among older adults, unattended dogs, lighting at night, and religious institutions were positively while steep slope was negatively associated with their walking. For younger adults, traffic speed (negative, -), public transportation (positive, +), malls (-), cultural/recreational destinations (+), schools (+), and resource production land uses such as farms and mines (-) were significant correlates of utilitarian walking. Conclusion: Different characteristics of NE are associated with utilitarian walking among younger vs. older adults in US rural towns. Optimal modifications of NE to promote walking may need to reflect these age differences., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lee, Lee, Stewart, Carlos, Adachi-Mejia, Berke and Doescher.)

Background: COVID-19 test sensitivity and specificity have been widely examined and discussed, yet optimal use of these tests will depend on the goals of testing, the population or setting, and the anticipated underlying disease prevalence. We model various combinations of key variables to identify and compare a range of effective and practical surveillance strategies for schools and businesses., Methods: We coupled a simulated data set incorporating actual community prevalence and test performance characteristics to a susceptible, infectious, removed (SIR) compartmental model, modeling the impact of base and tunable variables including test sensitivity, testing frequency, results lag, sample pooling, disease prevalence, externally-acquired infections, symptom checking, and test cost on outcomes including case reduction and false positives., Findings: Increasing testing frequency was associated with a non-linear positive effect on cases averted over 100 days. While precise reductions in cumulative number of infections depended on community disease prevalence, testing every 3 days versus every 14 days (even with a lower sensitivity test) reduces the disease burden substantially. Pooling provided cost savings and made a high-frequency approach practical; one high-performing strategy, testing every 3 days, yielded per person per day costs as low as $1.32., Interpretation: A range of practically viable testing strategies emerged for schools and businesses. Key characteristics of these strategies include high frequency testing with a moderate or high sensitivity test and minimal results delay. Sample pooling allowed for operational efficiency and cost savings with minimal loss of model performance., Competing Interests: Authors [GL, NS, CK, DG, EB] are employees of UnitedHealth Group; GL, NS, CK, and EB own stock in the company. DG is employed as the Senior Infectious Disease Fellow at UnitedHealth Group, Inc and serves as the Chief of Infectious Diseases for ProHealth NY an Optum Company. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Residents of long-term care facilities are at risk for coronavirus disease. We report a surveillance exercise at such a facility in Pennsylvania, USA. After introduction of a testing strategy and other measures, this facility had a 17-fold lower coronavirus disease case rate than neighboring facilities.

Both polyester and foam nasal swabs were collected from convalescent COVID-19 patients at a single visit and stored in viral transport media (VTM), saline or dry. Sensitivity of each swab material and media combination were estimated, three by three tables were constructed to measure polyester and foam concordance, and cycle threshold (Ct) values were compared. 126 visits had polyester and foam swabs stored in viral transport media (VTM), 51 had swabs stored in saline, and 63 had a foam swab in VTM and a polyester swab stored in a dry tube. Polyester and foam swabs had an estimated sensitivity of 87.3% and 94.5% respectively in VTM, 87.5% and 93.8% respectively in saline, and 75.0% and 90.6% respectively for dry polyester and foam VTM. Polyester and foam Ct values were correlated, but polyester showed decreased performance for cases with a viral load near the detection threshold and higher Ct values on average., Competing Interests: Brian Hart, Rachel Jennings, Prateek Verma, Deneen Vojta, and Ethan Berke were employees of UnitedHealth Group during the design and analysis of the study and initial drafting of the manuscript. Yuan-Po Tu is an employee of The Everett Clinic, which is a subsidiary of UnitedHealth Group. Leah R. Padgett and Douglas Rains are employees of Quantigen Biosciences and have performed contract services for Thermo Fisher Scientific. The specific roles of these authors are articulated in the ‘author contributions’ section. The competing interests implied by the authors’ employer/employee relationships do not alter our adherence to PLOS ONE policies on sharing data and materials.

Studies examining associations between weight status and neighborhood built environment (BE) have shown inconsistent results and have generally focused on urban settings. However, many Americans do not live in metropolitan areas and BE impacts may be different outside of metropolitan areas. We sought to examine whether the relationship between body mass index (BMI) and neighborhood BE exists and varies by geographic region across small towns in the United States. We conducted telephone surveys with 2156 adults and geographic information systems data in nine towns located within three geographic regions (Northeast, Texas, Washington) in 2011 and 2012. Multiple regression models examined the relationship between individual BMI and BE measures. Most physical activity variables were significantly associated with lower BMI in all geographic regions. We saw variation across geographic region in the relationship between characteristics of the BE variables and BMI. Some perceived and objectively-measured characteristics of the BE were significantly associated with adult BMI, but significant relationships varied by geographic region. For example, in the Northeast, perceived attractiveness of the neighborhood as a reason for why they chose to live there was associated with lower BMI; in Texas, the perceived presence of a fast food restaurant was negatively associated with BMI; in Washington, perceived presence of trees along the streets was associated with lower BMI. Our findings suggest that regional variation plays a role in the relationship between adult BMI and BE characteristics in small towns. Regardless of geographic location, interventions should encourage utilitarian walking and other forms of physical activity., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Walking among Latinos in US Micropolitan towns may vary by language spoken., Methods: In 2011-2012, we collected telephone survey and built environment (BE) data from adults in six towns located within micropolitan counties from two states with sizable Latino populations. We performed mixed-effects logistic regression modeling to examine relationships between ethnicity-language group [Spanish-speaking Latinos (SSLs); English-speaking Latinos (ESLs); and English-speaking non-Latinos (ENLs)] and utilitarian walking and recreational walking, accounting for socio-demographic, lifestyle and BE characteristics., Results: Low-income SSLs reported higher amounts of utilitarian walking than ENLs (p = 0.007), but utilitarian walking in this group decreased as income increased. SSLs reported lower amounts of recreational walking than ENLs (p = 0.004). ESL-ENL differences were not significant. We identified no statistically significant interactions between ethnicity-language group and BE characteristics., Discussion: Approaches to increase walking in micropolitan towns with sizable SSL populations may need to account for this group's differences in walking behaviors.

Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the nine BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data - often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols.

Objectives: The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns., Methods: In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations., Results: Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p<0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use., Conclusions: Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population., (Copyright © 2014 Elsevier Inc. All rights reserved.)

As research examining the effect of the built environment on health accelerates, it is critical for health and planning researchers to conduct studies and make recommendations in the context of a robust theoretical framework. We propose a framework for built environment change (BEC) related to improving health. BEC consists of elements of the built environment, how people are exposed to and interact with them perceptually and functionally, and how this exposure may affect health-related behaviours. Integrated into this framework are the legal and regulatory mechanisms and instruments that are commonly used to effect change in the built environment. This framework would be applicable to medical research as well as to issues of policy and community planning.

Introduction: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level., Methods: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status., Results: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class., Conclusions: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

In food-environment research, an alternative to resource-intensive direct observation on the ground has been the use of commercial business lists. We sought to determine how well a frequently used commercial business list measures a dense urban food environment like the Bronx, NY. On 155 Bronx street segments, investigators compared two different levels for matches between the business list and direct ground observation: lenient (by business type) and strict (by business name). For each level of matching, researchers calculated sensitivities and positive predictive values (PPVs) for the business list overall and by broad business categories: General Grocers (eg, supermarkets), Specialty Food Stores (eg, produce markets), Restaurants, and Businesses Not Primarily Selling Food (eg, newsstands). Even after cleaning the business list (eg, for cases of multiple listings at a single location), and allowing for inexactness in listed street addresses and spellings of business names, the overall performance of the business list was poor. For strict matches, the business list had an overall sensitivity of 39.3% and PPV of 45.5%. Sensitivities and PPVs by broad business categories were not meaningfully different from overall values, although sensitivity for General Grocers and PPV for Specialty Food Stores were particularly low: 26.2% and 32%, respectively. For lenient matches, sensitivities and PPVs were somewhat higher but still poor: 52.4% to 60% and 60% to 75%, respectively. The business list is inadequate to measure the actual food environment in the Bronx. If results represent performance in other settings, findings from prior studies linking food environments to diet and diet-related health outcomes using such business lists are in question, and future studies of this type should avoid relying solely on such business lists., (Copyright © 2013 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.)

Objective: To elucidate how demographics of US Census tracts are related to tobacco outlet density (TOD)., Method: The authors conducted a nationwide assessment of the association between socio-demographic US Census indicators and the density of tobacco outlets across all 64,909 census tracts in the continental USA. Retail tobacco outlet addresses were determined through North American Industry Classification System codes, and density per 1000 population was estimated for each census tract. Independent variables included urban/rural; proportion of the population that was black, Hispanic and women with low levels of education; proportion of families living in poverty and median household size., Results: In a multivariate analysis, there was a higher TOD per 1000 population in urban than in rural locations. Furthermore, higher TOD was associated with larger proportions of blacks, Hispanics, women with low levels of education and with smaller household size. Urban-rural differences in the relation between demographics and TOD were found in all socio-demographic categories, with the exception of poverty, but were particularly striking for Hispanics, for whom the relation with TOD was 10 times larger in urban compared with rural census tracts., Conclusions: The findings suggest that tobacco outlets are more concentrated in areas where people with higher risk for negative health outcomes reside. Future studies should examine the relation between TOD and smoking, smoking cessation, as well as disease rates.

This study identifies factors associated with walking among postmenopausal women and tests whether neighborhood walkability moderates the influence of intrapersonal factors on walking. We used data from the Women's Health Initiative Seattle Center and linear regression models to estimate associations and interactions. Being white and healthy, having a high school education or beyond and greater non-walking exercise were significantly associated with more walking. Neighborhood walkability was not independently associated with greater walking, nor did it moderate influence of intrapersonal factors on walking. Specifying types of walking (e.g., for transportation) can elucidate the relationships among intrapersonal factors, the built environment, and walking., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Objectives: To compare individual with community risk factors for adolescent smoking., Design: A cross-sectional observational study with multivariate analysis., Setting: National telephone survey., Participants: 3646 US adolescents aged 13-18 years in 2007 recruited through a random digit-dial survey., Outcome Measures: Ever tried smoking and, among experimental smokers, smoking intensity (based on smoking in past 30 days)., Results: One-third of participants (35.6%, N=1297) had tried smoking. After controlling for individual risk factors, neither tobacco outlet density nor proximity were associated with tried smoking or smoking intensity. Associations with trying smoking included age (adjusted OR (AOR)=1.23, 95% CI 1.16 to 1.31), lower socioeconomic status (AOR=0.82, 95% CI 0.74 to 0.91), sibling smoking (AOR=2.13, 95% CI 1.75 to 2.59), friend smoking (AOR=2.60, 95% CI 2.19 to 3.10 for some and AOR=7.01, 95% CI 5.05 to 9.74 for most), movie smoking exposure (AOR=2.66, 95% CI 1.95 to 3.63), team sports participation (AOR=0.69, 95% CI 0.54 to 0.89) and sensation seeking (AOR=7.72, 95% CI 5.26 to 11.34). Among experimental smokers, age (AOR=1.32, 95% CI 1.21 to 1.44), minority status (AOR=0.48, 95% CI 0.30 to 0.79 for Black; AOR=0.46, 95% CI 0.31 to 0.69 for Hispanic; AOR=0.53, 95% CI 0.43 to 0.85 for mixed race/other), friend smoking (AOR=3.37, 95% CI 2.37 to 4.81 for some; AOR=20.27, 95% CI 13.22 to 31.08 for most), team sports participation (AOR=0.38, 95% CI 0.26 to 0.55) and sensation seeking (AOR=6.57, 95% CI 3.71 to 11.64) were associated with smoking intensity., Conclusions: The study suggests that interventions and policies to prevent and reduce youth smoking should focus on individual risk factors for smoking, including supporting participation in team sports, minimising exposure to movie smoking, addressing the social influence of friend smoking and addressing experience seeking among high sensation-seekers.

Studies have shown that cancer care near the end of life is more aggressive than many patients prefer. Using a cohort of deceased Medicare beneficiaries with poor-prognosis cancer, meaning that they were likely to die within a year, we examined the association between hospital characteristics and eleven end-of-life care measures, such as hospice use and hospitalization. Our study revealed a relatively high intensity of care in the last weeks of life. At the same time, there was more than a twofold variation within hospital groups with common features, such as cancer center designation and for-profit status. We found that these hospital characteristics explained little of the observed variation in intensity of end-of-life cancer care and that none reliably predicted a specific pattern of care. These findings raise questions about what factors may be contributing to this variation. They also suggest that best practices in end-of-life cancer care can be found in many settings and that efforts to improve the quality of end-of-life care should include every hospital category.

Purpose: Automated systems able to infer detailed measures of a person's social interactions and physical activities in their natural environments could lead to better understanding of factors influencing well-being. We assessed the feasibility of a wireless mobile device in measuring sociability and physical activity in older adults, and compared results with those of traditional questionnaires., Methods: This pilot observational study was conducted among a convenience sample of 8 men and women aged 65 years or older in a continuing care retirement community. Participants wore a waist-mounted device containing sensors that continuously capture data pertaining to behavior and environment (accelerometer, microphone, barometer, and sensors for temperature, humidity, and light). The sensors measured time spent walking level, up or down an elevation, and stationary (sitting or standing), and time spent speaking with 1 or more other people. The participants also completed 4 questionnaires: the 36-Item Short Form Health Survey (SF-36), the Yale Physical Activity Survey (YPAS), the Center for Epidemiologic Studies-Depression (CES-D) scale, and the Friendship Scale., Results: Men spent 21.3% of their time walking and 64.4% stationary. Women spent 20.7% of their time walking and 62.0% stationary. Sensed physical activity was correlated with aggregate YPAS scores (r(2)=0.79, P=.02). Sensed time speaking was positively correlated with the mental component score of the SF-36 (r(2)=0.86, P = .03), and social interaction as assessed with the Friendship Scale (r(2)=0.97, P = .002), and showed a trend toward association with CES-D score (r(2)=-0.75, P = .08). In adjusted models, sensed time speaking was associated with SF-36 mental component score (P = .08), social interaction measured with the Friendship Scale (P = .045), and CES-D score (P=.04)., Conclusions: Mobile sensing of sociability and activity is well correlated with traditional measures and less prone to biases associated with questionnaires that rely on recall. Using mobile devices to collect data from and monitor older adult patients has the potential to improve detection of changes in their health.

Background: Geographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable areal unit problem and 2) any corresponding data must be available both at the scale of analysis and in the same geographic units. Kernel density estimation (KDE) produces a smooth, continuous surface where each location in the study area is assigned a density value irrespective of arbitrary administrative boundaries. We review KDE, and introduce the technique of utilizing an adaptive bandwidth to address the underlying heterogeneous population distributions common in public health research., Results: The density of occurrences should not be interpreted without knowledge of the underlying population distribution. When the effect of the background population is successfully accounted for, differences in point patterns in similar population areas are more discernible; it is generally these variations that are of most interest. A static bandwidth KDE does not distinguish the spatial extents of interesting areas, nor does it expose patterns above and beyond those due to geographic variations in the density of the underlying population. An adaptive bandwidth method uses background population data to calculate a kernel of varying size for each individual case. This limits the influence of a single case to a small spatial extent where the population density is high as the bandwidth is small. If the primary concern is distance, a static bandwidth is preferable because it may be better to define the "neighborhood" or exposure risk based on distance. If the primary concern is differences in exposure across the population, a bandwidth adapting to the population is preferred., Conclusions: Kernel density estimation is a useful way to consider exposure at any point within a spatial frame, irrespective of administrative boundaries. Utilization of an adaptive bandwidth may be particularly useful in comparing two similarly populated areas when studying health disparities or other issues comparing populations in public health.

Context: Several classification systems exist for defining rural areas, which may lead to different interpretations of rural health services data., Purpose: To compare rural classification systems on their implications for estimating Veterans Administration (VA) utilization., Methods: Using 7 classification systems, we counted VA health care enrollees who lived in each category, and number admitted to VA hospitals or non-VA hospitals under Medicare. For dual VA-Medicare enrollees over age 65, we compared VA and private sector hospitalizations on numbers of admissions and bed-days of care. We compared VA enrollees' relative proportions across rural to urban categories for each classification system and evaluated discordance between systems at the veterans-integrated service networks (VISN) level., Findings: Enrollment and inpatient utilization counts for rural veterans vary considerably from one classification system to another, though the systems generally agree that admission rates, length of stay, and reliance on the VA for care are lower for rural veterans. Among older dual VA and Medicare enrollees, rural residents rely on non-VA facilities more, though this effect also varies widely depending on the classification scheme. VISNs vary greatly in the proportions of patients who are rural residents, and in the degree to which classification systems are discordant in designating patients as rural., Conclusions: Decisions about allocating VA health care resources to target "rural" patients may be affected greatly by the rural classification system chosen, and the impact of this choice will affect some hospital networks much more than others.

Background: Travel time is an important metric of geographic access to health care. We compared strategies of estimating travel times when only subject ZIP code data were available., Results: Using simulated data from New Hampshire and Arizona, we estimated travel times to nearest cancer centers by using: 1) geometric centroid of ZIP code polygons as origins, 2) population centroids as origin, 3) service area rings around each cancer center, assigning subjects to rings by assuming they are evenly distributed within their ZIP code, 4) service area rings around each center, assuming the subjects follow the population distribution within the ZIP code. We used travel times based on street addresses as true values to validate estimates. Population-based methods have smaller errors than geometry-based methods. Within categories (geometry or population), centroid and service area methods have similar errors. Errors are smaller in urban areas than in rural areas., Conclusion: Population-based methods are superior to the geometry-based methods, with the population centroid method appearing to be the best choice for estimating travel time. Estimates in rural areas are less reliable.

Objectives: End-of-life care is increasingly recognized as an important part of cancer management for many patients. Current methods to measure end-of-life care are limited by difficulties in identifying cancer cohorts with administrative data. We examined several techniques of identifying end-of-life cancer cohorts with claims data that is population-based, geographically scalable, and amenable to routine updating., Methods: Using Medicare claims for patients 65 years of age and older, four techniques for identifying end-of-life cancer cohorts were compared; one based on Part A data using a broad primary or narrow secondary diagnosis of cancer, two based on Part B data, and one combining the Part A and B methods. We tested the performance of each definition to ascertain an appropriate end-of-life cancer population., Results: The combined Part A and B definition using a primary or secondary diagnosis of cancer within a window of 180 days prior to death appears to be the most accurate and inclusive in ascertaining an end-of-life cohort (78.7% attainment)., Conclusion: Combining inpatient and outpatient claims data, and identifying cases based upon a broad primary or a narrow secondary cancer definition is the most accurate and inclusive in ascertaining an end-of-life cohort.

Objectives: To determine whether participation in a physical activity benefit by Medicare managed care enrollees is associated with lower healthcare utilization and costs., Design: Retrospective cohort study., Setting: Medicare managed care., Participants: A cohort of 1,188 older adult health maintenance organization enrollees who participated at least once in the EnhanceFitness (EF) physical activity benefit and a matched group of enrollees who never used the program., Measurements: Healthcare costs and utilization were estimated. Ordinary least squares regression was used, adjusting for demographics, comorbidity, indicators of preventive service use, and baseline utilization or cost. Robustness of findings was tested in sensitivity analyses involving continuous propensity score adjustment and generalized linear models with nonconstant variance assumptions., Results: EF participants had similar total healthcare costs during Year 1 of the program, but during Year 2, adjusted total costs were $1,186 lower (P=.005) than for non-EF users. Differences were partially attributable to lower inpatient costs (-$3,384; P=.02), which did not result from high-cost outliers. Enrollees who attended EF an average of one visit or more per week had lower adjusted total healthcare costs in Year 1 (-$1,929; P<.001) and Year 2 (-$1,784; P<.001) than nonusers., Conclusion: Health plan coverage of a preventive physical activity benefit for seniors is a promising strategy to avoid significant healthcare costs in the short term.

Background: Environments conducive to walking may help people avoid sedentary lifestyles and associated diseases. Recent studies developed walkability models combining several built environment characteristics to optimally predict walking. Developing and testing such models with the same data could lead to overestimating one's ability to predict walking in an independent sample of the population. More accurate estimates of model fit can be obtained by splitting a single study population into training and validation sets (holdout approach) or through developing and evaluating models in different populations. We used these two approaches to test whether built environment characteristics near the home predict walking for exercise. Study participants lived in western Washington State and were adult members of a health maintenance organization. The physical activity data used in this study were collected by telephone interview and were selected for their relevance to cardiovascular disease. In order to limit confounding by prior health conditions, the sample was restricted to participants in good self-reported health and without a documented history of cardiovascular disease., Results: For 1,608 participants meeting the inclusion criteria, the mean age was 64 years, 90 percent were white, 37 percent had a college degree, and 62 percent of participants reported that they walked for exercise. Single built environment characteristics, such as residential density or connectivity, did not significantly predict walking for exercise. Regression models using multiple built environment characteristics to predict walking were not successful at predicting walking for exercise in an independent population sample. In the validation set, none of the logistic models had a C-statistic confidence interval excluding the null value of 0.5, and none of the linear models explained more than one percent of the variance in time spent walking for exercise. We did not detect significant differences in walking for exercise among census areas or postal codes, which were used as proxies for neighborhoods., Conclusion: None of the built environment characteristics significantly predicted walking for exercise, nor did combinations of these characteristics predict walking for exercise when tested using a holdout approach. These results reflect a lack of neighborhood-level variation in walking for exercise for the population studied.

Objectives: To evaluate the association between neighborhood walkability and depression in older adults., Design: Cross-sectional analysis using data from Adult Changes in Thought (ACT), a prospective, longitudinal cohort study., Setting: King County, Washington., Participants: Seven hundred forty randomly selected men and women aged 65 and older, cognitively intact, living in the same home for at least 2 years., Measurements: Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale. The Walkable and Bikable Communities Project provided objective data predicting the probability of walking at least 150 minutes per week in a particular neighborhood. ACT data were linked at the individual level via a geographic information system to this walkability score using buffer radii of 100, 500, and 1,000 meters around the subject's home. Multiple regression analysis tests were conducted for associations between the buffer-specific neighborhood walkability score and depressive symptoms., Results: There was a significant association between neighborhood walkability and depressive symptoms in men when adjusted for individual-level factors of income, physical activity, education, smoking status, living alone, age, ethnicity, and chronic disease. The odds ratio for the interquartile range (25th to 75th percentile) of walkability score was 0.31 to 0.33 for the buffer radii (P=.02), indicating a protective association with neighborhood walkability. This association was not significant in women., Conclusion: This study demonstrates a significant association between neighborhood walkability and depressive symptoms in older men. Further research on the effects of neighborhood walkability may inform community-level mental health treatment and focus depression screening in less-walkable areas.

Objective: We examined whether older persons who live in areas that are conducive to walking are more active or less obese than those living in areas where walking is more difficult., Methods: We used data from the Adult Changes in Thought cohort study for a cross-sectional analysis of 936 participants aged 65 to 97 years. The Walkable and Bikable Communities Project previously formulated a walkability score to predict the probability of walking in King County, Washington. Data from the cohort study were linked to the walkability score at the participant level using a geographic information system. Analyses tested for associations between walkability score and activity and body mass index., Results: Higher walkability scores were associated with significantly more walking for exercise across buffers (circular zones around each respondent's home) of varying radii (for men, odds ratio [OR]=5.86; 95% confidence interval [CI]=1.01, 34.17 to OR=9.14; CI=1.23, 68.11; for women, OR=1.63; CI=0.94, 2.83 to OR=1.77; CI=1.03, 3.04). A trend toward lower body mass index in men living in more walkable neighborhoods did not reach statistical significance., Conclusions: Findings suggest that neighborhood characteristics are associated with the frequency of walking for physical activity in older people. Whether frequency of walking reduces obesity prevalence is less clear.

Objective: The purpose of this article was to determine the effects of a managed-Medicare physical activity benefit on health care utilization and costs among older adults with diabetes., Research Design and Methods: This retrospective cohort study used administrative and claims data for 527 patients from a diabetes registry of a staff model HMO. Participants (n = 163) were enrolled in the HMO for at least 1 year before joining the Enhanced Fitness Program (EFP), a community-based physical activity program for which the HMO pays for each EFP class attended. Control subjects were matched to participants according to the index date of EFP enrollment (n = 364). Multivariate regression models were used to determine 12-month postindex differences in health care use and costs between participants and control subjects while adjusting for age, sex, chronic disease burden, EFP attendance, prevention score, heart registry, and respective baseline use and costs., Results: Participants and control subjects were similar at baseline with respect to age (75 +/- 5.5 years), A1C levels (7.4 +/- 1.4%), chronic disease burden, prevention score, and health care use and costs. After exposure to the program, there was a trend toward lower hospital admissions in EFP participants compared with control subjects (13.5 vs. 20.9%, P = 0.08), whereas total health care costs were not different (P = 0.39). EFP participants who attended > or = 1 exercise session/week on average had approximately 41% less total health care costs compared with those attending <1 session/week (P = 0.03) and with control subjects (P = 0.02)., Conclusions: Although elective participation in a community-based physical activity benefit at any level was not associated with lower inpatient or total health care costs, greater participation in the program may lower health care costs. These findings warrant additional investigations to determine whether policies to offer and promote a community-based physical activity benefit in older adults with diabetes can reduce health care costs.

This study evaluated the effect of distance on the likelihood of initiating and maintaining regular use of a fitness-program benefit in a population of managed Medicare seniors. We studied 8,162 participants and nonparticipants in a managed-care fitness-program benefit: a structured group exercise program or an unstructured health-club membership. Participants in both programs lived significantly closer to facilities than nonparticipants did (structured, p < .001; unstructured, p = .017). Participants living closer to unstructured-program sites attended more frequently than those farther away (p = .008). Distance was not correlated with frequency of use in the structured program (p = .49). Collectively, these analyses demonstrate that distance is related to uptake and, in some cases, continued use of a fitness-program benefit. Health systems providing fitness-program benefits as a way to increase physical activity levels of their plan members should consider location of program facilities in relation to members' home addresses to maximize use of the benefit.

It has been suggested that changes in fat-free weight may not fully explain the decline of resting metabolic rate (RMR) that occurs with aging. We therefore examined the hypothesis that a reduction in maximal aerobic capacity (VO2max) may partially explain the lower RMR in older men, after accounting for differences in fat-free weight and fat weight. We also considered differences in energy intake and plasma thyroid hormones as possible modulators of the age-related decline in RMR in men. Three-hundred healthy men (aged 17 to 78 years) were characterized for: (1) RMR (kcal/min) from indirect calorimetry; (2) body composition from underwater weighing; (3) maximal aerobic capacity from a test of VO2max; (4) plasma thyroid hormones (total triiodothyronine [T3], free T3, total thyroxine [T4], and free T4); and (5) estimated energy intake (kcal/d) from a 3-day food diary. A curvilinear decline of RMR with age was found (P less than .01), in which no relationship was found in men less than 40 years of age (r = .10, slope = 0.002 kcal/min/yr), whereas in men older than 40 years, RMR was negatively related to age (r = -.52, slope = -0.008 kcal/min/yr). After statistical control for differences in fat-free weight and fat weight, a negative relationship between age and RMR persisted (partial r = -.30, P less than .01). It was only after control for fat-free weight, fat weight, and VO2max (partial r = -.10, P greater than .05) that no association between age and RMR was noted.(ABSTRACT TRUNCATED AT 250 WORDS)