Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women.

BACKGROUND: Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution. METHODS: We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses' Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses. RESULTS: Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season. DISCUSSION: We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

Shigella sonnei Outbreak Investigation During a Municipal Water Crisis-Genesee and Saginaw Counties, Michigan, 2016.

Objectives. To investigate a shigellosis outbreak in Genesee County, Michigan (including the City of Flint), and Saginaw County, Michigan, in 2016 and address community concerns about the role of the Flint water system.Methods. We met frequently with community members to understand concerns and develop the investigation. We surveyed households affected by the outbreak, analyzed Shigella isolate data, examined the geospatial distribution of cases, and reviewed available water quality data.Results. We surveyed 83 households containing 158 cases; median age was 10 years. Index case-patients from 55 of 83 households (66%) reported contact with a person outside their household who wore diapers or who had diarrhea in the week before becoming ill; results were similar regardless of household drinking water source. Genomic diversity was not consistent with a point source. In Flint, no space-time clustering was identified, and average free chlorine residual values remained above recommended levels throughout the outbreak period.Conclusions. The outbreak was most likely caused by person-to-person contact and not by the Flint water system. Consistent community engagement was essential to the design and implementation of the investigation.

Transforming geographic scale: a comparison of combined population and areal weighting to other interpolation methods.

BACKGROUND: Transforming spatial data from one scale to another is a challenge in geographic analysis. As part of a larger, primary study to determine a possible association between travel barriers to pediatric cancer facilities and adolescent cancer mortality across the United States, we examined methods to estimate mortality within zones at varying distances from these facilities: (1) geographic centroid assignment, (2) population-weighted centroid assignment, (3) simple areal weighting, (4) combined population and areal weighting, and (5) geostatistical areal interpolation. For the primary study, we used county mortality counts from the National Center for Health Statistics (NCHS) and population data by census tract for the United States to estimate zone mortality. In this paper, to evaluate the five mortality estimation methods, we employed address-level mortality data from the state of Georgia in conjunction with census data. Our objective here is to identify the simplest method that returns accurate mortality estimates. RESULTS: The distribution of Georgia county adolescent cancer mortality counts mirrors the Poisson distribution of the NCHS counts for the U.S. Likewise, zone value patterns, along with the error measures of hierarchy and fit, are similar for the state and the nation. Therefore, Georgia data are suitable for methods testing. The mean absolute value arithmetic differences between the observed counts for Georgia and the five methods were 5.50, 5.00, 4.17, 2.74, and 3.43, respectively. Comparing the methods through paired t-tests of absolute value arithmetic differences showed no statistical difference among the methods. However, we found a strong positive correlation (r = 0.63) between estimated Georgia mortality rates and combined weighting rates at zone level. Most importantly, Bland-Altman plots indicated acceptable agreement between paired arithmetic differences of Georgia rates and combined population and areal weighting rates. CONCLUSIONS: This research contributes to the literature on areal interpolation, demonstrating that combined population and areal weighting, compared to other tested methods, returns the most accurate estimates of mortality in transforming small counts by county to aggregated counts for large, non-standard study zones. This conceptually simple cartographic method should be of interest to public health practitioners and researchers limited to analysis of data for relatively large enumeration units.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction.

BACKGROUND: Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI). OBJECTIVE: The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI. METHODS: We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM2.5) and nitrogen dioxide (NO2), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification. RESULTS: Among 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO2 increase and suggestive positive associations were observed for PM2.5, lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO2, PM2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature. CONCLUSION: We observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures.

County-level social vulnerability and nonfatal drug overdose emergency department visits and hospitalizations, January 2018-December 2020.

BACKGROUND: Nonfatal drug overdoses (NFODs) are often attributed to individual behaviors and risk factors; however, identifying community-level social determinants of health (SDOH) associated with increased NFOD rates may allow public health and clinical providers to develop more targeted interventions to address substance use and overdose health disparities. CDC's Social Vulnerability Index (SVI), which aggregates social vulnerability data from the American Community Survey to produce ranked county-level vulnerability scores, can help identify community factors associated with NFOD rates. This study aims to describe associations between county-level social vulnerability, urbanicity, and NFOD rates. METHODS: We analyzed county-level 2018-2020 emergency department (ED) and hospitalization discharge data submitted to CDC's Drug Overdose Surveillance and Epidemiology system. Counties were ranked in vulnerability quartiles based on SVI data. We used crude and adjusted negative binomial regression models, by drug category, to calculate rate ratios and 95% confidence intervals comparing NFOD rates by vulnerability. RESULTS: Generally, as social vulnerability scores increased, ED and hospitalization NFOD rates increased; however, the magnitude of the association varied across drugs, visit type, and urbanicity. SVI-related theme and individual variable analyses highlighted specific community characteristics associated with NFOD rates. CONCLUSIONS: The SVI can help identify associations between social vulnerabilities and NFOD rates. Development of an overdose-specific validated index could improve translation of findings to public health action. The development and implementation of overdose prevention strategies should consider a socioecological perspective and address health inequities and structural barriers associated with increased risk of NFODs at all levels of the social ecology.

Association between passively collected walking and bicycling data and purposefully collected active commuting survey data-United States, 2019.

Commercially-available location-based services (LBS) data derived primarily from mobile devices may provide an alternative to surveys for monitoring physically-active transportation. Using Spearman correlation, we compared county-level metrics of walking and bicycling from StreetLight with metrics of physically-active commuting among U.S. workers from the American Community Survey. Our strongest pair of metrics ranked counties (n = 298) similarly for walking (rho = 0.53 [95% CI: 0.44-0.61]) and bicycling (rho = 0.61 [0.53-0.67]). Correlations were higher for denser and more urban counties. LBS data may offer public health and transportation professionals timely information on walking and bicycling behavior at finer geographic scales than some existing surveys.

Area-Based Sociodemographic Factors Associated with Latent Tuberculosis Infection in a Low-Prevalence Setting.

Area-based sociodemographic markers, such as census tract foreign-born population, have been used to identify individuals and communities with a high risk for tuberculosis (TB) infection in the United States. However, these markers have not been evaluated as independent risk factors for TB infection in children. We evaluated associations between census tract poverty, crowding, foreign-born population, and the CDC's Social Vulnerability Index (CDC-SVI) ranking and TB infection in a population of children tested for TB infection in Boston, Massachusetts. After adjustment for age, crowding, and foreign-born percentage, increasing census tract poverty was associated with increased odds of TB infection (adjusted odds ratio [aOR] per 10% increase in population proportion living in poverty: 1.20 [95% CI, 1.04-1.40]; P = 0.01), although this association was attenuated after further adjustment for preferred language. In separate models, increasing CDC-SVI ranking was associated with increased odds of TB infection, including after adjustment for age and language preference (aOR per 10-point increase in CDC-SVI rank: 1.08 [95% CI, 1.02-1.15]; P = 0.01). Our findings suggest area-based sociodemographic factors may be valuable for characterizing TB infection risk and defining the social ecology of pediatric TB infection in low-burden settings.

Association between Outdoor Light at Night and Prostate Cancer in the Health Professionals Follow-up Study.

BACKGROUND: Circadian disruption is a potential risk factor for advanced prostate cancer, and light at night (LAN) exposure may disrupt circadian rhythms. We evaluated whether outdoor LAN increases the risk of prostate cancer. METHODS: We prospectively followed 49,148 participants in the Health Professionals Follow-up Study from 1986 through 2016. We estimated baseline and cumulative time-varying outdoor LAN with ∼1 km2 resolution using data from the US Defense Meteorological Satellite Program's Operational Linescan System, which was assigned to participants' geocoded addresses. Participants reside in all 50 U.S. states and reported a work or home address. We used multivariable Cox models to estimate HRs and 95% confidence intervals (CI) for the association between outdoor LAN and risk of overall (7,175 cases) and fatal (915 cases) prostate cancer adjusting for individual and contextual factors. RESULTS: There was no association between the interquartile range increase in cumulative LAN and total (HR, 1.02; 95% CI, 0.98-1.06) or fatal (HR, 1.05; 95% CI, 0.96-1.15) prostate cancer in adjusted models. However, there was a positive association between baseline LAN and total prostate cancer among non-movers (HR, 1.06; 95% CI, 1.00-1.14) including among highly screened participants (HR, 1.11; 95% CI, 1.01-1.23). CONCLUSIONS: There was a suggestive positive association between baseline outdoor LAN and total prostate cancer. Additional studies with different measures of outdoor LAN and in more diverse populations are necessary. IMPACT: To our knowledge, this is the first longitudinal cohort study exploring the relationship between outdoor LAN and prostate cancer.

Air Pollution and Temperature: a Systematic Review of Ubiquitous Environmental Exposures and Sudden Cardiac Death.

PURPOSE OF REVIEW: Environmental exposures have been associated with increased risk of cardiovascular mortality and acute coronary events, but their relationship with out-of-hospital cardiac arrest (OHCA) and sudden cardiac death (SCD) remains unclear. SCD is an important contributor to the global burden of cardiovascular disease worldwide. RECENT FINDINGS: Current literature suggests a relationship between environmental exposures and cardiovascular disease, but their relationship with OHCA/SCD remains unclear. A literature search was conducted in PubMed, Embase, Web of Science, and Global Health. Of 5138 studies identified by our literature search, this review included 30 studies on air pollution, 42 studies on temperature, 6 studies on both air pollution and temperature, and 1 study on altitude exposure and OHCA/SCD. Particulate matter air pollution, ozone, and both hot and cold temperatures are associated with increased risk of OHCA/SCD. Pollution and other exposures related to climate change play an important role in OHCA/SCD incidence.

Geographic Associations Between Social Factors and SARS-CoV-2 Testing Early in the COVID-19 Pandemic, February-June 2020, Massachusetts.

OBJECTIVES: Widespread SARS-CoV-2 testing is critical to identify infected people and implement public health action to interrupt transmission. With SARS-CoV-2 testing supplies and laboratory capacity now widely available in the United States, understanding the spatial heterogeneity of associations between social determinants and the use of SARS-CoV-2 testing is essential to improve testing availability in populations disproportionately affected by SARS-CoV-2. METHODS: We assessed positive and negative results of SARS-CoV-2 molecular tests conducted from February 1 through June 17, 2020, from the Massachusetts Virtual Epidemiologic Network, an integrated web-based surveillance and case management system in Massachusetts. Using geographically weighted regression and Moran's I spatial autocorrelation tests, we quantified the associations between SARS-CoV-2 testing rates and 11 metrics of the Social Vulnerability Index in all 351 towns in Massachusetts. RESULTS: Median SARS-CoV-2 testing rates decreased with increasing percentages of residents with limited English proficiency (median relative risk [interquartile range] = 0.96 [0.95-0.99]), residents aged ≥65 (0.97 [0.87-0.98]), residents without health insurance (0.96 [0.95-1.04], and people residing in crowded housing conditions (0.89 [0.80-0.94]). These associations differed spatially across Massachusetts, and localized models improved the explainable variation in SARS-CoV-2 testing rates by 8% to 12%. CONCLUSION: Indicators of social vulnerability are associated with variations in SARS-CoV-2 testing rates. Accounting for the spatial heterogeneity in these associations may improve the ability to explain and address the SARS-CoV-2 pandemic at substate levels.

Associations between Nature Exposure and Health: A Review of the Evidence.

There is extensive empirical literature on the association between exposure to nature and health. In this narrative review, we discuss the strength of evidence from recent (i.e., the last decade) experimental and observational studies on nature exposure and health, highlighting research on children and youth where possible. We found evidence for associations between nature exposure and improved cognitive function, brain activity, blood pressure, mental health, physical activity, and sleep. Results from experimental studies provide evidence of protective effects of exposure to natural environments on mental health outcomes and cognitive function. Cross-sectional observational studies provide evidence of positive associations between nature exposure and increased levels of physical activity and decreased risk of cardiovascular disease, and longitudinal observational studies are beginning to assess long-term effects of nature exposure on depression, anxiety, cognitive function, and chronic disease. Limitations of current knowledge include inconsistent measures of exposure to nature, the impacts of the type and quality of green space, and health effects of duration and frequency of exposure. Future directions include incorporation of more rigorous study designs, investigation of the underlying mechanisms of the association between green space and health, advancement of exposure assessment, and evaluation of sensitive periods in the early life-course.

Social Vulnerability and Access of Local Medical Care During Hurricane Harvey: A Spatial Analysis.

OBJECTIVES: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. METHODS: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. RESULTS: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. CONCLUSIONS: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.

Time Spent in Nature Is Associated with Increased Pro-Environmental Attitudes and Behaviors.

Urbanization, screen dependency, and the changing nature of childhood and parenting have led to increased time indoors, creating physical and emotional distancing from nature and time spent in natural environments. Substantial evidence from observational and intervention studies indicates that overall time spent in nature leads to increased perceived value for connectedness to nature and, subsequently, greater pro-environmental attitudes and behaviors (PEAB). This narrative review of the recent literature evaluates associations between time spent in nature with values ascribed to nature and nature connectedness, as well as PEAB. We discuss the influence of nature exposure and education in childhood on subsequent development of PEAB in adulthood. We analyze theoretical frameworks applied to this research as well as metrics employed, populations studied, and individual and societal values before presenting limitations of this research. We conclude with suggestions for future research directions based on current knowledge, underscoring the importance of promoting time spent in nature and PEAB in the face of growing challenges to planetary health. Research indicates that overall time spent in nature, regardless of the quality of environmental conditions, leads to increased perceived values ascribed to nature, which is associated with PEAB; however, this literature is predominantly cross-sectional. Furthermore, personal and social factors may influence PEAB. Thus, more longitudinal studies that consider these factors are needed to assess the duration and frequency of time spent in nature in childhood and its impact on PEAB throughout the life course. Identifying contexts which cultivate PEAB and reverse alienation from nature beginning in childhood may better sensitize adults to the urgency of environmental issues such as climate change, which adversely impact individual and environmental health.

Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7-April 20, 2020.

PURPOSE: Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. METHODS: Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7-April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). RESULTS: Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. CONCLUSIONS: Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Spatial exploration of the CDC's Social Vulnerability Index and heat-related health outcomes in Georgia.

Heat-related illness, an environmental exposure-related outcome commonly treated in U.S. hospital emergency departments (ED), is likely to rise with increased incidence of heat events related to climate change. Few studies demonstrate the spatial and statistical relationship of social vulnerability and heat-related health outcomes. We explore relationships of Georgia county-level heat-related ED visits and mortality rates (2002-2008), with CDC's Social Vulnerability Index (CDC SVI). Bivariate Moran's I analysis revealed significant clustering of high SVI rank and high heat-related ED visit rates (0.211, p < 0.001) and high smoothed mortality rates (0.210, p < 0.001). Regression revealed that for each 10% increase in SVI ranking, ED visit rates significantly increased by a factor of 1.18 (95% CI = 1.17-1.19), and mortality rates significantly increased by a factor of 1.31 (95% CI = 1.16-1.47). CDC SVI values are spatially linked and significantly associated with heat-related ED visit, and mortality rates in Georgia.

A Spatial and Temporal Investigation of Medical Surge in Dallas-Fort Worth During Hurricane Harvey, Texas 2017.

OBJECTIVE: When 2017 Hurricane Harvey struck the coastline of Texas on August 25, 2017, it resulted in 88 fatalities and more than US $125 billion in damage to infrastructure. The floods associated with the storm created a toxic mix of chemicals, sewage and other biohazards, and over 6 million cubic meters of garbage in Houston alone. The level of biohazard exposure and injuries from trauma among persons residing in affected areas was widespread and likely contributed to increases in emergency department (ED) visits in Houston and cities receiving hurricane evacuees. We investigated medical surge resulting from these evacuations in Dallas-Fort Worth (DFW) metroplex EDs. METHODS: We used data sourced from the North Texas Syndromic Surveillance Region 2/3 in ESSENCE to investigate ED visit surge following the storm in DFW hospitals because this area received evacuees from the 60 counties with disaster declarations due to the storm. We used the interrupted time series (ITS) analysis to estimate the magnitude and duration of the ED surge. ITS was applied to all ED visits in DFW and visits made by patients residing in any of the 60 counties with disaster declarations due to the storm. The DFW metropolitan statistical area included 55 hospitals. Time series analyses examined data from March 1, 2017-January 6, 2018 with focus on the storm impact period, August 14-September 15, 2017. Data from before, during, and after the storm were visualized spatially and temporally to characterize magnitude, duration, and spatial variation of medical surge attributable to Hurricane Harvey. RESULTS: During the study period overall, ED visits in the DFW area rose immediately by about 11% (95% CI: 9%, 13%), amounting to ~16 500 excess total visits before returning to the baseline on September 21, 2017. Visits by patients identified as residing in disaster declaration counties to DFW hospitals rose immediately by 127% (95% CI: 125%, 129%), amounting to 654 excess visits by September 29, 2017, when visits returned to the baseline. A spatial analysis revealed that evacuated patients were strongly clustered (Moran's I = 0.35, P < 0.0001) among 5 of the counties with disaster declarations in the 11-day window during the storm surge. CONCLUSIONS: The observed increase in ED visits in DFW due to Hurricane Harvey and ensuing evacuation was significant. Anticipating medical surge following large-scale hurricanes is critical for community preparedness planning. Coordinated planning across stakeholders is necessary to safeguard the population and for a skillful response to medical surge needs. Plans that address hurricane response, in particular, should have contingencies for support beyond the expected disaster areas.

Sociodemographic disparities in access to ovarian cancer treatment.

BACKGROUND: Ovarian cancer is the fifth most common cause of cancer death among women in the United States. Failure to receive optimal treatment and poorer survival rates have been reported for older women, African-American women, women with low income, and women with public health insurance coverage or no coverage. Additionally, regional differences in geographic access influence the type of treatment women may seek. This paper explores geographic accessibility and sociodemographic vulnerability in Georgia, which influence receipt of optimal ovarian cancer treatment. METHODS: An enhanced two-step floating catchment area (E2SFCA), defining physical access, was created for each census tract and gynecologic oncologist clinic. Secondly, sociodemographic variables reflecting potential social vulnerability were selected from U.S. Census and American Community Survey data at the tract level. These two measures were combined to create a measure of Geosocial Vulnerability. This framework was tested using Georgia ovarian cancer mortality records. RESULTS: Geospatial access was higher in urban areas with less accessibility in suburban and rural areas. Sociodemographic vulnerability varied geospatially, with higher vulnerability in urban citers and rural areas. Sociodemographic measures were combined with geospatial access to create a Geosocial Vulnerability Indicator, which showed a significant positive association with ovarian cancer mortality. CONCLUSIONS: Spatial and sociodemographic measures pinpointed areas of healthcare access vulnerability not revealed by either spatial analysis or sociodemographic assessment alone. Whereas lower healthcare accessibility in rural areas has been well described, our analysis shows considerable heterogeneity in access to care in urban areas where the disadvantaged census tracts can be easily identified.

Geographic Access to Cancer Care and Mortality Among Adolescents.

PURPOSE: Adolescents with cancer have had less improvement in survival than other populations in the United States. This may be due, in part, to adolescents not receiving treatment at Children's Oncology Group (COG) institutions, which have been shown to increase survival for some cancers. The objective of this ecologic study was to examine geographic distance to COG institutions and adolescent cancer mortality. METHODS: We calculated cancer mortality among adolescents and sociodemographic and healthcare access factors in four geographic zones at selected distances surrounding COG facilities: Zone A (area within 10 miles of any COG institution), Zones B and C (concentric rings with distances from a COG institution of >10-25 miles and >25-50 miles, respectively), and Zone D (area outside of 50 miles). RESULTS: The adolescent cancer death rate was highest in Zone A at 3.21 deaths/100,000, followed by Zone B at 3.05 deaths/100,000, Zone C at 2.94 deaths/100,000, and Zone D at 2.88 deaths/100,000. The United States-wide death rate for whites without Hispanic ethnicity, blacks without Hispanic ethnicity, and persons with Hispanic ethnicity was 2.96 deaths/100,000, 3.10 deaths/100,000, and 3.26 deaths/100,000, respectively. Zone A had high levels of poverty (15%), no health insurance coverage (16%), and no vehicle access (16%). CONCLUSIONS: Geographic access to COG institutions, as measured by distance alone, played no evident role in death rate differences across zones. Among adolescents, socioeconomic factors, such as poverty and health insurance coverage, may have a greater impact on cancer mortality than geographic distance to COG institution.

Vulnerabilities Associated with Post-disaster Declines in HIV-testing: Decomposing the Impact of Hurricane Sandy.

INTRODUCTION: Using Interrupted Time Series Analysis and generalized estimating equations, this study identifies factors that influence the size and significance of Hurricane Sandy's estimated impact on HIV testing in 90 core-based statistical areas from January 1, 2011 to December 31, 2013. METHODS: Generalized estimating equations were used to examine the effects of sociodemographic and storm-related variables on relative change in HIV testing resulting from Interrupted Time Series analyses. RESULTS: There is a significant negative relationship between HIV prevalence and the relative change in testing at all time periods. A one unit increase in HIV prevalence corresponds to a 35% decrease in relative testing the week of the storm and a 14% decrease in relative testing at week twelve. Building loss was also negatively associated with relative change for all time points. For example, a one unit increase in building loss at week 0 corresponds with an 8% decrease in the relative change in testing (p=0.0001) and a 2% at week twelve (p=0.001). DISCUSSION: Our results demonstrate that HIV testing can be negatively affected during public health emergencies. Communities with high percentages of building loss and significant HIV disease burden should prioritize resumption of testing to support HIV prevention.