Neighborhood Recreation Facilities and Facility Membership Are Jointly Associated with Objectively Measured Physical Activity.

Efforts to increase physical activity have traditionally included either individual-level interventions (e.g., educational campaigns) or neighborhood-level interventions (e.g., additional recreational facilities). Little work has addressed the interaction between spatial proximity and individual characteristics related to facility use. We aimed to better understand the synergistic impact of both physical activity environments and recreational facility membership on objectively measured physical activity. Using the New York City Physical Activity and Transit (PAT) survey (n = 644), we evaluated associations between counts of commercial physical activity facilities within 1 km of participants' home addresses with both facility membership and accelerometry-measured physical activity. Individuals living near more facilities were more likely to report membership (adjusted odds ratio for top versus bottom quartile of facility count: 3.77 (95% CI 1.54-9.20). Additionally, while amount of facilities within a neighborhood was associated with more physical activity, this association was stronger for individuals reporting gym membership. Interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership. Evaluation of neighborhood opportunities must expand beyond physical presence to consider multiple dimensions of accessibility.

A Local View of Informal Urban Environments: a Mobile Phone-Based Neighborhood Audit of Street-Level Factors in a Brazilian Informal Community.

Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. A smartphone-based systematic observation protocol was used to gather street-level information for a high-density convenience sample of street segments (N = 630, estimated as 86% of all street segments in the community). We adapted items related to physical disorder and physical deterioration. Measures selected to illustrate the approach include the presence of the following: (1) low-hanging or tangled wires, (2) litter, (3) structural evidence of sinking, and (4) an unpleasant odor. Intercept-only spatial generalized additive models (GAM) were used to evaluate and visualize spatial variation within the RdP community. We also examined how our estimates and conclusions about spatial variation might have been affected by lower-density sampling from random subsets street observations. Random subsets were selected to determine the robustness of study results in scenarios with sparser street sampling. Selected characteristics were estimated to be present for between 18% (unpleasant odor) to 59% (low-hanging or tangled wires) of the street segments in RdP; estimates remain similar (± 6%) when relying on a random subset created to simulate lower-density spatial sampling. Spatial patterns of variation based on predicted probabilities across RdP differed by indicator. Structural sinking and low-hanging or tangled wires demonstrated relatively consistent spatial distribution patterns across full and random subset sample sizes. Smartphone-based systematic observations represent an efficient and potentially feasible approach to systematically studying neighborhood environments within informal communities. Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras.

Associations of Residential Socioeconomic, Food, and Built Environments With Glycemic Control in Persons With Diabetes in New York City From 2007-2013.

In the present study, we examined the longitudinal associations between residential environmental factors and glycemic control in 182,756 adults with diabetes in New York City from 2007 to 2013. Glycemic control was defined as a hemoglobin A1c (HbA1c) level less than 7%. We constructed residential-level measures and performed principle component analysis to formulate a residential composite score. On the basis of this score, we divided residential areas into quintiles, with the lowest and highest quintiles reflecting the least and most advantaged residential environments, respectively. Several residential-level environmental characteristics, including more advantaged socioeconomic conditions, greater ratio of healthy food outlets to unhealthy food outlets, and residential walkability were associated with increased glycemic control. Individuals who lived continuously in the most advantaged residential areas took less time to achieve glycemic control compared with the individuals who lived continuously in the least advantaged residential areas (9.9 vs. 11.5 months). Moving from less advantaged residential areas to more advantaged residential areas was related to improved diabetes control (decrease in HbA1c = 0.40%, 95% confidence interval: 0.22, 0.55), whereas moving from more advantaged residential areas to less advantaged residential areas was related to worsening diabetes control (increase in HbA1c = 0.33%, 95% confidence interval: 0.24, 0.44). These results show that residential areas with greater resources to support healthy food and residential walkability are associated with improved glycemic control in persons with diabetes.

Street Audits to Measure Neighborhood Disorder: Virtual or In-Person?

Neighborhood conditions may influence a broad range of health indicators, including obesity, injury, and psychopathology. In particular, neighborhood physical disorder-a measure of urban deterioration-is thought to encourage crime and high-risk behaviors, leading to poor mental and physical health. In studies to assess neighborhood physical disorder, investigators typically rely on time-consuming and expensive in-person systematic neighborhood audits. We compared 2 audit-based measures of neighborhood physical disorder in the city of Detroit, Michigan: One used Google Street View imagery from 2009 and the other used an in-person survey conducted in 2008. Each measure used spatial interpolation to estimate disorder at unobserved locations. In total, the virtual audit required approximately 3% of the time required by the in-person audit. However, the final physical disorder measures were significantly positively correlated at census block centroids (r = 0.52), identified the same regions as highly disordered, and displayed comparable leave-one-out cross-validation accuracy. The measures resulted in very similar convergent validity characteristics (correlation coefficients within 0.03 of each other). The virtual audit-based physical disorder measure could substitute for the in-person one with little to no loss of precision. Virtual audits appear to be a viable and much less expensive alternative to in-person audits for assessing neighborhood conditions.

Quantifying Distance Overestimation From Global Positioning System in Urban Spaces.

OBJECTIVES: To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City. METHODS: We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System-measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk. RESULTS: GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy). CONCLUSIONS: Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques.

Use of Google Street View to Assess Environmental Contributions to Pedestrian Injury.

OBJECTIVES: To demonstrate an information technology-based approach to assess characteristics of streets and intersections associated with injuries that is less costly and time-consuming than location-based studies of pedestrian injury. METHODS: We used imagery captured by Google Street View from 2007 to 2011 to assess 9 characteristics of 532 intersections within New York City. We controlled for estimated pedestrian count and estimated the relation between intersections' characteristics and frequency of injurious collisions. RESULTS: The count of pedestrian injuries at intersections was associated with the presence of marked crosswalks (80% increase; 95% confidence interval [CI] = 2%, 218%), pedestrian signals (156% increase; 95% CI = 69%, 259%), nearby billboards (42% increase; 95% CI = 7%, 90%), and bus stops (120% increase; 95% CI = 51%, 220%). Injury incidence per pedestrian was lower at intersections with higher estimated pedestrian volumes. CONCLUSIONS: Consistent with in-person study observations, the information-technology approach found traffic islands, visual advertising, bus stops, and crosswalk infrastructures to be associated with elevated counts of pedestrian injury in New York City. Virtual site visits for pedestrian injury control studies are a viable and informative methodology.

Neighborhood food environment, dietary fatty acid biomarkers, and cardiac arrest risk.

We explored links between food environments, dietary intake biomarkers, and sudden cardiac arrest in a population-based longitudinal study using cases and controls accruing between 1990 and 2010 in King County, WA. Surprisingly, presence of more unhealthy food sources near home was associated with a lower 18:1 trans-fatty acid concentration (-0.05% per standard deviation higher count of unhealthy food sources, 95% Confidence Interval [CI]: 0.01, 0.09). However, presence of more unhealthy food sources was associated with higher odds of cardiac arrest (Odds Ratio [OR]: 2.29, 95% CI: 1.19, 4.41 per standard deviation in unhealthy food outlets). While unhealthy food outlets were associated with higher cardiac arrest risk, circulating 18:1 trans fats did not explain the association.

Using GPS Data to Study Neighborhood Walkability and Physical Activity.

INTRODUCTION: Urban form characteristics intended to support pedestrian activity, collectively referred to as neighborhood walkability, are thought to increase total physical activity. However, little is known about how neighborhood walkability influences utilization of neighborhood space by residents and their overall physical activity. METHODS: Sociodemographic information and data on mobility and physical activity over 1-week periods measured by GPS loggers and accelerometers were collected from 803 residents of New York City between November 2010 and November 2011. Potentially accessible neighborhood areas were defined as land area within a 1-kilometer distance of the subject's home (radial buffer) and within a 1-kilometer journey on the street network from the home (network buffer). To define actual areas utilized by subjects, a minimum convex polygon was plotted around GPS waypoints falling within 1 kilometer of the home. A neighborhood walkability scale was calculated for each neighborhood area. Data were analyzed in 2014. RESULTS: Total residential neighborhood space utilized by subjects was significantly associated with street intersection density and was significantly negatively associated with residential density and subway stop density within 1 kilometer of the home. Walkability scale scores were significantly higher within utilized as compared with non-utilized neighborhood areas. Neighborhood walkability in the utilized neighborhood area was positively associated with total weekly physical activity (32% [95% CI=17%, 49%] more minutes of moderate-equivalent physical activity across the interquartile range of walkability). CONCLUSION: Neighborhood walkability is associated with neighborhood spaces utilized by residents and total weekly physical activity.

Neighborhood Physical Disorder in New York City.

Neighborhood physical disorder, or the deterioration of urban environments, is associated with negative mental and physical health outcomes. Eleven trained raters used CANVAS, a web-based system for conducting reliable virtual street audits, to collect data on nine indicators of physical disorder using Google Street View imagery of 532 block faces in New York City, New York, USA. We combined the block face indicator data into a disorder scale using item response theory; indicators ranged in severity from presence of litter, a weak indicator of disorder, to abandoned cars, a strong indicator. Using this scale, we estimated disorder at the center point of each sampled block. We then used ordinary kriging to interpolate estimates of disorder levels throughout the city. The resulting map condenses a complex estimation process into an interpretable visualization of the spatial distribution of physical disorder in New York City.

Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set.

BACKGROUND: The densities of food retailers, alcohol outlets, physical activity facilities, and medical facilities have been associated with diet, physical activity, and management of medical conditions. Most of the research, however, has relied on cross-sectional studies. In this paper, we assess methodological issues raised by a data source that is increasingly used to characterize change in the local business environment: the National Establishment Time Series (NETS) dataset. DISCUSSION: Longitudinal data, such as NETS, offer opportunities to assess how differential access to resources impacts population health, to consider correlations among multiple environmental influences across the life course, and to gain a better understanding of their interactions and cumulative health effects. Longitudinal data also introduce new data management, geoprocessing, and business categorization challenges. Examining geocoding accuracy and categorization over 21 years of data in 23 counties surrounding New York City (NY, USA), we find that health-related business environments change considerably over time. We note that re-geocoding data may improve spatial precision, particularly in early years. Our intent with this paper is to make future public health applications of NETS data more efficient, since the size and complexity of the data can be difficult to exploit fully within its 2-year data-licensing period. Further, standardized approaches to NETS and other "big data" will facilitate the veracity and comparability of results across studies.

Goitrogenic and estrogenic activity of soy isoflavones.

Soy is known to produce estrogenic isoflavones. Here, we briefly review the evidence for binding of isoflavones to the estrogen receptor, in vivo estrogenicity and developmental toxicity, and estrogen developmental carcinogenesis in rats. Genistein, the major soy isoflavone, also has a frank estrogenic effect in women. We then focus on evidence from animal and human studies suggesting a link between soy consumption and goiter, an activity independent of estrogenicity. Iodine deficiency greatly increases soy antithyroid effects, whereas iodine supplementation is protective. Thus, soy effects on the thyroid involve the critical relationship between iodine status and thyroid function. In rats consuming genistein-fortified diets, genistein was measured in the thyroid at levels that produced dose-dependent and significant inactivation of rat and human thyroid peroxidase (TPO) in vitro. Furthermore, rat TPO activity was dose-dependently reduced by up to 80%. Although these effects are clear and reproducible, other measures of thyroid function in vivo (serum levels of triiodothyronine, thyroxine, and thyroid-stimulating hormone; thyroid weight; and thyroid histopathology) were all normal. Additional factors appear necessary for soy to cause overt thyroid toxicity. These clearly include iodine deficiency but may also include additional soy components, other defects of hormone synthesis, or additional goitrogenic dietary factors. Although safety testing of natural products, including soy products, is not required, the possibility that widely consumed soy products may cause harm in the human population via either or both estrogenic and goitrogenic activities is of concern. Rigorous, high-quality experimental and human research into soy toxicity is the best way to address these concerns. Similar studies in wildlife populations are also appropriate.

Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts.

A number of environmental chemicals, by mimicking natural hormones, can disrupt endocrine function in experimental animals, wildlife, and humans. These chemicals, called "endocrine-disrupting chemicals" (EDCs), are such a scientific and public concern that screening and testing 58,000 chemicals for EDC activities is now statutorily mandated. Computational chemistry tools are important to biologists because they identify chemicals most important for in vitro and in vivo studies. Here we used a computational approach with integration of two rejection filters, a tree-based model, and three structural alerts to predict and prioritize estrogen receptor (ER) ligands. The models were developed using data for 232 structurally diverse chemicals (training set) with a 10(6) range of relative binding affinities (RBAs); we then validated the models by predicting ER RBAs for 463 chemicals that had ER activity data (testing set). The integrated model gave a lower false negative rate than any single component for both training and testing sets. When the integrated model was applied to approximately 58,000 potential EDCs, 80% (approximately 46,000 chemicals) were predicted to have negligible potential (log RBA < -4.5, with log RBA = 2.0 for estradiol) to bind ER. The ability to process large numbers of chemicals to predict inactivity for ER binding and to categorically prioritize the remainder provides one biologic measure to prioritize chemicals for entry into more expensive assays (most chemicals have no biologic data of any kind). The general approach for predicting ER binding reported here may be applied to other receptors and/or reversible binding mechanisms involved in endocrine disruption.

Developing a laboratory animal model for perinatal endocrine disruption: the hamster chronicles.

At the biomedical, regulatory, and public level, considerable concern surrounds the concept that inappropriate exposure to endocrine-disrupting chemicals, especially during the prenatal and/or neonatal period, may disrupt normal reproductive tract development and adult function. The intent of this review was to 1. Describe some unique advantages of the hamster for perinatal endocrine disruptor (ED) studies, 2. Summarize the morphological and molecular consequences of exposure to the established perinatal ED, diethylstilbestrol, in the female and male hamster, 3. Present some new, histomorphological insight into the process of neonatal diethylstilbestrol-induced disruption in the hamster uterus, and 4. Introduce recent efforts and future plans to evaluate the potency and mechanism of action of other putative EDs in the hamster experimental system. Taken together, the findings indicate that the hamster represents a unique and sensitive in vivo system to probe the phenomenon of endocrine disruption. The spectrum of candidate endpoints includes developmental toxicity, neoplasia, and more subtle endpoints of reproductive dysfunction.

No-threshold dose-response curves for nongenotoxic chemicals: findings and applications for risk assessment.

We tested the hypothesis that no threshold exists when estradiol acts through the same mechanism as an active endogenous estrogen. A Michaelis-Menten (MM) equation accounting for response saturation, background effects, and endogenous estrogen level fit a turtle sex-reversal data set with no threshold and estimated the endogenous dose. Additionally, 31 diverse literature dose-response data sets were analyzed by adding a term for nonhormonal background; good fits were obtained but endogenous dose estimations were not significant due to low resolving power. No thresholds were observed. Data sets were plotted using a normalized MM equation; all 178 data points were accommodated on a single graph. Response rates from approximately 1% to >95% were well fit. The findings contradict the threshold assumption and low-dose safety. Calculating risk and assuming additivity of effects from multiple chemicals acting through the same mechanism rather than assuming a safe dose for nonthresholded curves is appropriate.

Diethylstilbestrol versus estradiol as neonatal disruptors of the hamster (Mesocricetus auratus) cervix.

The synthetic estrogen diethylstilbestrol (DES) is an established, estrogenic endocrine disruptor (ED). The Syrian golden hamster (Mesocricetus auratus) offers some unique advantages as an experimental system to investigate the perinatal ED action of DES and other estrogenic EDs. Previous analyses regarding the consequences of neonatal administration (100 microg) of DES versus estradiol-17beta (E2) showed that DES had a more potent disruptive effect on morphogenesis and gene expression in the uterus, oviduct, and ovary as well as in the testis and male accessory organs. The objectives of the present study were to describe the histopathological consequences of the two neonatal treatment regimens in the hamster cervix and to compare them with our previous observations in the hamster uterus. As previously found in the hamster uterus, DES was more potent than E2 as a neonatal disruptor of the hamster cervix in prepubertal animals and in ovarian-intact adult animals. However, the cervix-versus-uterus scenario diverged in animals that were ovariectomized prepubertally and then chronically stimulated with natural estrogen (E2). We confirmed previous observations that neonatal exposure to DES, but not to E2, permanently alters estrogen responsiveness in the adult hamster uterus, but neither neonatal treatment regimen affected estrogen responsiveness in the adult hamster cervix. These results suggest that an unidentified ovarian factor influences the extent of neonatal DES-induced disruption of the cervix, but not of the uterus, in hamsters.

Study of 202 natural, synthetic, and environmental chemicals for binding to the androgen receptor.

A number of environmental and industrial chemicals are reported to possess androgenic or antiandrogenic activities. These androgenic endocrine disrupting chemicals may disrupt the endocrine system of humans and wildlife by mimicking or antagonizing the functions of natural hormones. The present study developed a low cost recombinant androgen receptor (AR) competitive binding assay that uses no animals. We validated the assay by comparing the protocols and results from other similar assays, such as the binding assay using prostate cytosol. We tested 202 natural, synthetic, and environmental chemicals that encompass a broad range of structural classes, including steroids, diethylstilbestrol and related chemicals, antiestrogens, flutamide derivatives, bisphenol A derivatives, alkylphenols, parabens, alkyloxyphenols, phthalates, siloxanes, phytoestrogens, DDTs, PCBs, pesticides, organophosphate insecticides, and other chemicals. Some of these chemicals are environmentally persistent and/or commercially important, but their AR binding affinities have not been previously reported. To the best of our knowledge, these results represent the largest and most diverse data set publicly available for chemical binding to the AR. Through a careful structure-activity relationship (SAR) examination of the data set in conjunction with knowledge of the recently reported ligand-AR crystal structures, we are able to define the general structural requirements for chemical binding to AR. Hydrophobic interactions are important for AR binding. The interaction between ligand and AR at the 3- and 17-positions of testosterone and R1881 found in other chemical classes are discussed in depth. The SAR studies of ligand binding characteristics for AR are compared to our previously reported results for estrogen receptor binding.

Phytoestrogens and mycoestrogens bind to the rat uterine estrogen receptor.

Consumption of phytoestrogens and mycoestrogens in food products or as dietary supplements is of interest because of both the potential beneficial and adverse effects of these compounds in estrogen-responsive target tissues. Although the hazards of exposure to potent estrogens such as diethylstilbestrol in developing male and female reproductive tracts are well characterized, less is known about the effects of weaker estrogens including phytoestrogens. With some exceptions, ligand binding to the estrogen receptor (ER) predicts uterotrophic activity. Using a well-established and rigorously validated ER-ligand binding assay, we assessed the relative binding affinity (RBA) for 46 chemicals from several chemical structure classes of potential phytoestrogens and mycoestrogens. Although none of the test compounds bound to ER with the affinity of the standard, 17beta-estradiol (E(2)), ER binding was found among all classes of chemical structures (flavones, isoflavones, flavanones, coumarins, chalcones and mycoestrogens). Estrogen receptor relative binding affinities were distributed across a wide range (from approximately 43 to 0.00008; E(2) = 100). These data can be utilized before animal testing to rank order estimates of the potential for in vivo estrogenic activity of a wide range of untested plant chemicals (as well as other chemicals) based on ER binding.