Multidimensional Approach to Exploring Neighborhood Determinants and Symptom Severity Among Individuals With Psychosis.

Importance: The impact of cumulative exposure to neighborhood factors on psychosis, depression, and anxiety symptom severity prior to specialized services for psychosis is unknown. Objective: To identify latent neighborhood profiles based on unique combinations of social, economic, and environmental factors, and validate profiles by examining differences in symptom severity among individuals with first episode psychosis (FEP). Design, Setting, and Participants: This cohort study used neighborhood demographic data and health outcome data for US individuals with FEP receiving services between January 2017 and August 2022. Eligible participants were between ages 14 and 40 years and enrolled in a state-level coordinated specialty care network. A 2-step approach was used to characterize neighborhood profiles using census-tract data and link profiles to mental health outcomes. Data were analyzed March 2023 through October 2023. Exposures: Economic and social determinants of health; housing conditions; land use; urbanization; walkability; access to transportation, outdoor space, groceries, and health care; health outcomes; and environmental exposure. Main Outcomes and Measures: Outcomes were Community Assessment of Psychic Experiences 15-item, Patient Health Questionnaire 9-item, and Generalized Anxiety Disorder 7-item scale. Results: The total sample included 225 individuals aged 14 to 36 years (mean [SD] age, 20.7 [4.0] years; 152 men [69.1%]; 9 American Indian or Alaska Native [4.2%], 13 Asian or Pacific Islander [6.0%], 19 Black [8.9%], 118 White [55.1%]; 55 Hispanic ethnicity [26.2%]). Of the 3 distinct profiles identified, nearly half of participants (112 residents [49.8%]) lived in urban high-risk neighborhoods, 56 (24.9%) in urban low-risk neighborhoods, and 57 (25.3%) in rural neighborhoods. After controlling for individual characteristics, compared with individuals residing in rural neighborhoods, individuals residing in urban high-risk (mean estimate [SE], 0.17 [0.07]; P = .01) and urban low-risk neighborhoods (mean estimate [SE], 0.25 [0.12]; P = .04) presented with more severe psychotic symptoms. Individuals in urban high-risk neighborhoods reported more severe depression (mean estimate [SE], 1.97 [0.79]; P = .01) and anxiety (mean estimate [SE], 1.12 [0.53]; P = .04) than those in rural neighborhoods. Conclusions and Relevance: This study found that in a cohort of individuals with FEP, baseline psychosis, depression, and anxiety symptom severity differed by distinct multidimensional neighborhood profiles that were associated with where individuals reside. Exploring the cumulative effect of neighborhood factors improves our understanding of social, economic, and environmental impacts on symptoms and psychosis risk which could potentially impact treatment outcomes.

Distance to endoscopy services amplifies racial inequities in colorectal cancer mortality in Washington state.

BACKGROUND: This study evaluates relationships among race, access to endoscopy services, and colorectal cancer (CRC) mortality in Washington state (WA). METHODS: We overlayed the locations of ambulatory endoscopy services with place of residence at time of death, using Department of Health data (2011-2018). We compared CRC mortality data within and outside a 10 â€‹km buffer from services. We used linear regression to assess the impact of distance and race on age at death while adjusting for gender and education level. RESULTS: Age at death: median 72.9y vs. 68.2y for white vs. non-white (p â€‹< â€‹0.001). The adjusted model showed that non-whites residing outside the buffer died 6.9y younger on average (p â€‹< â€‹0.001). Non-whites residing inside the buffer died 5.2y younger on average (p â€‹< â€‹0.001), and whites residing outside the buffer died 1.6y younger (p â€‹< â€‹0.001). We used heatmaps to geolocate death density. CONCLUSIONS: Results suggest that geographic access to endoscopy services disproportionately impacts non-whites in Washington. These data help identify communities which may benefit from improved access to alternative colorectal cancer screening methods.

Disparities in access to opioid treatment programs and buprenorphine providers by race and ethnicity in the contiguous U.S.

BACKGROUND: The burden of drug overdose mortality varies by race and ethnicity, with American Indian/Alaska Native (AI/AN), Black, and White people experiencing the largest burden. We analyzed census block group data to evaluate differences in travel distance to opioid treatment programs (OTP) and buprenorphine providers by race and ethnicity. METHODS: The Substance Abuse and Mental Health Services Administration provided the addresses of OTPs and buprenorphine providers. The study classified block groups as majority (≥50 %) AI/AN, Black, Asian, White, no single racial majority, or Hispanic. We classified deprivation and rurality using the Area Deprivation Index and Rural-Urban Commuting Area codes. The study applied generalized linear mixed models. RESULTS: Among all block groups, the median road distance to the nearest OTPs and buprenorphine providers was 8 and 2 miles, respectively. AI/AN-majority block groups had the longest median distances to OTPs (88 miles versus 4-10 miles) and buprenorphine providers (17 miles versus 1-3 miles) compared to other racial or ethnic majority block groups. For OTPs and buprenorphine providers, travel distances were slightly greater in more deprived block groups compared to less deprived block groups. The median distance to the nearest OTPs and buprenorphine providers were larger in micropolitan and small town/rural block groups compared to metropolitan areas. CONCLUSIONS: Disparities exist in travel distance to OTPs and buprenorphine providers. People in block groups with AI/AN-majority, nonmetropolitan, or more deprived designation experience travel disparities accessing treatment. Future research should develop targeted interventions to reduce access to care disparities for individuals with opioid use disorder.

Travel Burden to Cancer Screening and Treatment Facilities Among Washington Women: Data From an Integrated Healthcare Delivery System.

PURPOSE: To characterize distance traveled for breast cancer screening and to sites of service for breast cancer treatment, among rural and urban women served by a Washington State healthcare network. METHODS: Data for this study came from one of the largest not-for-profit integrated healthcare delivery systems in Washington State. Generalized linear mixed models with gamma log link function were used to examine the associations between travel distance and sociodemographic and contextual characteristics of patients. RESULTS: Median travel distance for breast cancer screening facilities, hematologist/oncologists, radiation oncologists, or surgeons was 11, 19, 23, or 11 miles, respectively. Travel distance to breast cancer screening or referral facilities was longer in non-core metropolitan ZIP codes compared to metropolitan ZIP codes. AI/AN and Hispanic women travelled longer distances to reach referral facilities compared to other racial and ethnic groups. CONCLUSION: Disparities exist in travel distance to breast cancer screening and treatment. Further research is needed to describe sociodemographic and system level characteristics that contribute to such disparities and to discover novel approaches to alleviate this burden.

Opioid use and COVID-19: a secondary analysis of the impact of relaxation of methadone take-home dosing guidelines on use of illicit opioids.

Background: An exemption to existing U.S. regulation of methadone maintenance therapy after the onset of the COVID-19 pandemic permitted increased take-home doses beginning March 2020.Objectives: We assessed the impact of this exemption on opioid use.Methods: A pre/post study of 187 clients recruited from an OTP who completed a survey and consented to share their urine drug testing (UDT) data. Use of fentanyl, morphine, hydromorphone, codeine, and heroin was assessed via UDT. Receipt of take-home methadone doses was assessed from clinic records for 142 working days pre- and post-COVID exemption. Analysis was conducted using a linear regression model to assess the association between increased take-home doses and use of illicit opioids.Results: In the pre- vs. post-COVID-19 SAMHSA exemption periods, 26.2% vs. 36.3% of UDTs were positive for 6-acetylmorphine respectively, 32.6% vs. 40.6% positive for codeine, 34.2% vs 44.2% positive for hydromorphone, 39.5% vs. 48.1% positive for morphine, 8.0% vs. 14.4% positive for fentanyl (p-value < .001). However, in the unadjusted descriptive data, when grouped by change in substance use, those clients who experienced a decrease in the use of morphine, codeine, and heroin post-COVID-19 were given significantly more take-home doses than the groups that had no change or an increase in the use of these substances. In the adjusted model, there was no significant relationship between change in opioid use and increased receipt of take-home methadone doses.Conclusions: Although take-home doses post-COVID-19 nearly doubled, this increase was not associated with a significant change in use of illicit opioids.

Changes to methadone maintenance therapy in the United States, Canada, and Australia during the COVID-19 pandemic: A narrative review.

INTRODUCTION: In response to the COVID-19 pandemic, countries across the world made adaptations to policies regulating the provision of methadone maintenance therapy (MMT) to facilitate social distancing for health care providers and people in treatment. Many countries issued guidance about increasing take-home methadone doses after the onset of the pandemic. METHODS: In this review, we compare the regulation of MMT prior to the pandemic in the United States, Canada, and Australia, analyze changes to treatment policy in the context of COVID-19, and review emerging data on treatment outcomes. RESULTS: The United States only permits the prescription and disbursement of methadone for MMT treatment at federally designated opioid treatment programs (OTPs). Conversely, Australia and Canada operate on a community pharmacy-based distribution model, where patients can access methadone doses either in participating pharmacies or in some methadone clinics. CONCLUSION: Given reports of similar treatment outcomes and increased patient satisfaction since the pandemic-related policy changes, some changes including increased receipt of take-home doses should be considered for incorporation into post-pandemic treatment policies and regulations.

Fulminant pulmonary tuberculosis in a previously healthy young woman from the Marshall Islands: Potential risk factors.

A 19-year-old woman originally from the Republic of the Marshall Islands presented with diffuse pneumonia and acute hypoxemic respiratory failure. She dies one month into her hospitalization but the diagnosis of pulmonary tuberculosis (TB) was not made until one day before her demise. A contact investigation screened a total of 155 persons with 36 (23%) found to have latent TB infection and seven (4.5%) with active pulmonary TB. This unfortunate case provided the opportunity to analyze the epidemiology of TB in the state of Washington in the context of those who emigrated from the Marshall Islands. The development of fulminant pulmonary TB in this previously healthy young woman also provides a segue to discuss potential risk factors for TB in the index case that include: (i) foreign-born in a TB-endemic country; (ii) race and genetic factors; (iii) age; (iv) body habitus; (v) pregnancy; and (vi) use of glucocorticoids.

Availability of timely methadone treatment in the United States and Canada during COVID-19: A census tract-level analysis.

OBJECTIVES: We sought to compare timely access to methadone treatment in the United States (US) and Canada during the COVID-19 pandemic. METHODS: We conducted a cross-sectional study of census tracts and aggregated dissemination areas (used for rural Canada) within 14 US and 3 Canadian jurisdictions in 2020. We excluded census tracts or areas with a population density of less than one person per square km. Data from a 2020 audit of timely medication access was used to determine clinics accepting new patients within 48 h. Unadjusted and adjusted linear regressions were performed to examine the relationship between area population density and sociodemographic covariates and three outcome variables: 1) driving distance to the nearest methadone clinic accepting new patients, 2) driving distance to the nearest methadone clinic accepting new patients for medication initiation within 48 h, and 3) the difference in the driving distance between the first and second outcome. RESULTS: We included 17,611 census tracts and areas with a population density greater than one person per square kilometer. After adjusting for area covariates, US jurisdictions were a median of 11.6 miles (p value <0.001) further from a methadone clinic accepting new patients and 25.1 miles (p value <0.001) further from a clinic accepting new patients within 48 h than Canadian jurisdictions. CONCLUSIONS: These results suggest that the more flexible Canadian regulatory approach to methadone treatment is associated with a greater availability of timely methadone treatment and reduced urban-rural disparity in availability, compared to the US.

Bring Your Own Location Data: Use of Google Smartphone Location History Data for Environmental Health Research.

BACKGROUND: Environmental exposures are commonly estimated using spatial methods, with most epidemiological studies relying on home addresses. Passively collected smartphone location data, like Google Location History (GLH) data, may present an opportunity to integrate existing long-term time-activity data. OBJECTIVES: We aimed to evaluate the potential use of GLH data for capturing long-term retrospective time-activity data for environmental health research. METHODS: We included 378 individuals who participated in previous Global Positioning System (GPS) studies within the Washington State Twin Registry. GLH data consists of location information that has been routinely collected since 2010 when location sharing was enabled within android operating systems or Google apps. We created instructions for participants to download their GLH data and provide it through secure data transfer. We summarized the GLH data provided, compared it to available GPS data, and conducted an exposure assessment for nitrogen dioxide (NO2) air pollution. RESULTS: Of 378 individuals contacted, we received GLH data from 61 individuals (16.1%) and 53 (14.0%) indicated interest but did not have historical GLH data available. The provided GLH data spanned 2010-2021 and included 34 million locations, capturing 66,677 participant days. The median number of days with GLH data per participant was 752, capturing 442 unique locations. When we compared GLH data to 2-wk GPS data (∼1.8 million points), 95% of GPS time-activity points were within 100m of GLH locations. We observed important differences between NO2 exposures assigned at home locations compared with GLH locations, highlighting the importance of GLH data to environmental exposure assessment. DISCUSSION: We believe collecting GLH data is a feasible and cost-effective method for capturing retrospective time-activity patterns for large populations that presents new opportunities for environmental epidemiology. Cohort studies should consider adding GLH data collection to capture historical time-activity patterns of participants, employing a "bring-your-own-location-data" citizen science approach. Privacy remains a concern that needs to be carefully managed when using GLH data. https://doi.org/10.1289/EHP10829.

Measuring and modelling perceptions of the built environment for epidemiological research using crowd-sourcing and image-based deep learning models.

BACKGROUND: Perceptions of the built environment, such as nature quality, beauty, relaxation, and safety, may be key factors linking the built environment to human health. However, few studies have examined these types of perceptions due to the difficulty in quantifying them objectively in large populations. OBJECTIVE: To measure and predict perceptions of the built environment from street-view images using crowd-sourced methods and deep learning models for application in epidemiologic studies. METHODS: We used the Amazon Mechanical-Turk crowdsourcing platform where participants compared two street-view images and quantified perceptions of nature quality, beauty, relaxation, and safety. We optimized street-view image sampling methods to improve the quality and resulting perception data specific to participants enrolled in the Washington State Twin Registry (WSTR) health study. We used a transfer learning approach to train deep learning models by leveraging existing image perception data from the PlacePulse 2.0 dataset, which includes 1.1 million image comparisons, and refining based on new WSTR perception data. Resulting models were applied to WSTR addresses to estimate exposures and evaluate associations with traditional built environment measures. RESULTS: We collected over 36,000 image comparisons and calculated perception measures for each image. Our final deep learning models explained 77.6% of nature quality, 68.1% of beauty, 72.0% of relaxation, and 64.7% of safety in pairwise image comparisons. Applying transfer learning with the new perception labels specific to the WSTR yielded an average improvement of 3.8% for model performance. Perception measures were weakly to moderately correlated with traditional built environment exposures for WSTR participant addresses; for example, nature quality and NDVI (r = 0.55), neighborhood area deprivation (r = -0.16), and walkability (r = -0.20), respectively. SIGNIFICANCE: We were able to measure and model perceptions of the built environment optimized for a specific health study. Future applications will examine associations between these exposure measures and mental health in the WSTR. IMPACT STATEMENT: Built environments influence health through complex pathways. Perceptions of nature quality, beauty, relaxation and safety may be particularly import for understanding these linkages, but few studies to-date have examined these perceptions objectively for large populations. For quantitative research, an exposure measure must be reproducible, accurate, and precise--here we work to develop such measures for perceptions of the urban environment. We created crowd-sourced and image-based deep learning methods that were able to measure and model these perceptions. Future applications will apply these models to examine associations with mental health in the Washington State Twin Registry.

Racial and socioeconomic inequities in breast cancer screening before and during the COVID-19 pandemic: analysis of two cohorts of women 50 years + .

BACKGROUND: Routine screening mammography at two-year intervals is widely recommended for the prevention and early detection of breast cancer for women who are 50 years + . Racial and other sociodemographic inequities in routine cancer screening are well-documented, but less is known about how these long-standing inequities were impacted by the disruption in health services during the COVID-19 pandemic. Early in the pandemic, cancer screening and other prevention services were suspended or delayed, and these disruptions may have had to disproportionate impact on some sociodemographic groups. We tested the hypothesis that inequities in screening mammography widened during the pandemic. METHODS: A secondary analysis of patient data from a large state-wide, non-profit healthcare system in Washington State. Analyses were based on two mutually exclusive cohorts of women 50 years or older. The first cohort (n = 18,197) were those women screened in 2017 who would have been due for repeat screening in 2019 (prior to the pandemic's onset). The second cohort (n = 16,391) were women screened in 2018 due in 2020. Explanatory variables were obtained from patient records and included race/ethnicity, age, rural or urban residence, and insurance type. Multivariable logistic regression models estimated odds of two-year screening for each cohort separately. Combining both cohorts, interaction models were used to test for differences in inequities before and during the pandemic. RESULTS: Significant sociodemographic differences in screening were confirmed during the pandemic, but these were similar to those that existed prior. Based on interaction models, women using Medicaid insurance and of Asian race experienced significantly steeper declines in screening than privately insured and white women (Odds ratios [95% CI] of 0.74 [0.58-0.95] and 0.76 [0.59-0.97] for Medicaid and Asian race, respectively). All other sociodemographic inequities in screening during 2020 were not significantly different from those in 2019. CONCLUSIONS: Our findings confirm inequities for screening mammograms during the first year of the COVID-19 pandemic and provide evidence that these largely reflect the inequities in screening that were present before the pandemic. Policies and interventions to tackle long-standing inequities in use of preventive services may help ensure continuity of care for all, but especially for racial and ethnic minorities and the socioeconomically disadvantaged.

COVID-19 and inequities in colorectal and cervical cancer screening and diagnosis in Washington State.

INTRODUCTION: Studies have shown that cancer screenings dropped dramatically following the onset of the coronavirus diseases 2019 (COVID-19) pandemic. In this study, we examined differences in rates of cervical and colorectal cancer (CRC) screening and diagnosis indicators before and during the first year of the COVID-19 pandemic. METHODOLOGY: We used retrospective data from a large healthcare system in Washington State. Targeted screening data included completed cancer screenings for both CRC (colonoscopy) and cervical cancer (Papanicolaou test (Pap test)). We analyzed and compared the rate of uptake of colorectal (colonoscopies) and cervical cancer (Pap) screenings done pre-COVID-19 (April 1, 2019-March 31, 2020) and during the pandemic (April 1, 2020-March 31, 2021). RESULTS: A total of 26,081 (12.7%) patients underwent colonoscopies in the pre-COVID-19 period, compared to only 15,708 (7.4%) patients during the pandemic, showing a 39.8% decrease. A total of 238 patients were referred to medical oncology for CRC compared to only 155 patients during the first year of the pandemic, a reduction of 34%. In the pre-COVID-19 period, 22,395 (10.7%) women were administered PAP tests compared to 20,455 (9.6%) women during the pandemic, for a 7.4% reduction. period 1780 women were referred to colposcopy, compared to only 1680 patients during the pandemic, for a 4.3% reduction. CONCLUSION: Interruption in screening and subsequent delay in diagnosis during the pandemic will likely lead to later-stage diagnoses for both CRC and cervical cancer, which is known to result in decreased survival. IMPACT: The results emphasize the need to prioritize cancer screening, particularly for those at higher risk.

Disparities in Access to Radiation Therapy Facilities Among American Indians/Alaska Natives and Hispanics in Washington State.

PURPOSE: Racial and ethnic minorities in the state of Washington experience higher cancer mortality relative to whites. We sought to characterize differences in travel distance to radiation therapy (RT) facilities in Washington by race and ethnicity with a special focus on non-Hispanic American Indians and Alaska Natives as a contributor to limited access and cancer disparities. METHODS AND MATERIALS: Geocoded mortality data from Washington Department of Health (2011-2018) were used to identify decedents with mortality related to all-causes, all cancers, and cancers likely requiring access to RT. This was determined from optimal RT usage estimates by diagnosis. RT facility locations were ascertained from the Directory of Radiation Therapy Centers and confirmed. Distance from decedents' address listed on death certificates to nearest RT facility was calculated. Generalized mixed models were used for statistical analysis. RESULTS: We identified 418,754 deaths; 109,134 were cancer-related, 60,973 likely required RT. Among decedents with cancers likely requiring RT, non-Hispanic American Indians and Alaska Natives decedents would have had to travel 1.16 times (95% confidence interval [CI], 1.09-1.24) farther from their residences to reach the nearest treatment facility compared with non-Hispanic whites. This association existed in metro counties but was more pronounced in nonmetro counties (1.39 times farther; 95% CI, 1.22-1.58). In addition, Hispanics would have had to travel 1.11 times farther (95% CI, 1.06-1.16) to reach the nearest facility compared with non-Hispanic whites, primarily due to differences in urban counties. Decedents in nonmetro counties lived on average 35 miles (SD = 29) from RT centers and non-Hispanic American Indians and Alaska Natives in nonmetro counties 53 miles (SD = 38). Compared with non-Hispanic white decedents, those who were non-Hispanic black, non-Hispanic Asian, and non-Hispanic Native Hawaiian decedents lived closer to RT facilities. CONCLUSIONS: We observed significant disparities in access to RT facilities in Washington, specifically for non-Hispanic American Indians and Alaska Natives and rural decedents. The findings call for initiatives to improve access to critical cancer treatment services for these underserved populations with known disparities in cancer deaths.

Changes in methadone take-home dosing before and after COVID-19.

INTRODUCTION: In response to the COVID-19 pandemic, a federal exemption allowed stable and less stable patients greater take-home doses of methadone. We assessed the adoption of increased take-home medication during COVID-19 and whether increased take-home doses is associated with clients' characteristics. METHODOLOGY: We completed a pre-post study of adults receiving methadone for OUD from an OTP in Spokane, Washington. Our outcome was the change in the number of take-home methadone doses three months before and three months after the March 2020 take-home medication exemption. Clients' characteristics included age, gender, ethnicity, education level, homelessness, spatial access to the clinic, and methamphetamine use. RESULTS: The study included 194 clients in treatment for a median of three years. All study participants experienced an average increase in take-home medication of 41.4 in the three-month period after the COVID-19 exemption. In the final adjusted models, clients who reported using methamphetamine in the last 30 days experienced a significantly larger increase in take-home dosage (55.6 days) compare to clients who did not use methamphetamine (p ≤0.001). Most of the clients who reported using methamphetamine were also likely to be homeless. All other variables were not associated with a change in take-home doses. CONCLUSION: These results suggest that the Spokane OTP quickly expanded take-home medication dosing in response to the COVID-19 exemption and broadly expanded take-home dosing among established clients. Clients with concurrent methamphetamine use were allowed fewer take-home doses prior to COVID-19, but after the exemption the clinic provided them the same number of take-home doses as clients who had not used methamphetamine.

The impact of relaxation of methadone take-home protocols on treatment outcomes in the COVID-19 era.

BACKGROUND: Background: In response to the COVID-19 pandemic, the US Substance Abuse and Mental Health Services Administration (SAMHSA) allowed for an increase in methadone take-home doses for the treatment of Opioid Use Disorder (OUD) in March 2020. OBJECTIVE: To evaluate the effects of the SAMSHA exemption on methadone adherence and OUD-related outcomes. METHODS: A convenience sample of 183 clients (58% female) were recruited from a methadone clinic in the fall of 2019 for a cross-sectional survey. Survey data was linked to clinical records, including urine drug testing (UDT) results for methadone and emergency department (ED) visits at the local hospital. Participants were on stable methadone dosing for 9 months prior to and following March 2020. Methadone adherence was assessed by UDTs; OUD-related outcomes were assessed by overdose events and ED visits. Logistic regression was used to assess the association between change in take-home methadone doses and outcomes. RESULTS: Mean take-home doses increased nearly 200% (11.4 doses/30 days pre-COVID-19 vs. 22.3 post-SAMHSA exemption). ED visits dropped from 74 (40.4%) pre-COVID-19 to 56 (30.6%) post-SAMHSA exemption (p = <0.001). No significant changes were observed in either the number of clients experiencing overdose or those who experienced one or more methadone negative UDTs in the post-SAMHSA exemption period. Adjusted models did not show a significant association between changes in take-home doses and associated outcomes. CONCLUSIONS: Despite a near-doubling of take-home methadone doses during the COVID-19 exemption period, the increase in take-home doses was not associated with negative treatment outcomes in methadone-adherent clients.

Media Exposure and Substance Use Increase during COVID-19.

BACKGROUND: Lockdown measures because of COVID-19 are likely to result in deteriorating physical and mental health. In this study, our aim was to assess the impact of media exposure on increases in substance use during the COVID-19 pandemic. METHODS: A nationally representative online survey of 1264 adults was collected during the pandemic in the United States. Logistic regression was used to explore the association between an increase in substance use since the beginning of the COVID-19 pandemic and exposure to cable news or social media together with COVID-19 knowledge, while controlling for covariates. RESULTS: In the multivariable-adjusted models, participants with the highest exposure to social media (at least daily) and low knowledge of COVID-19 were 9.9 times more likely to experience an increase in substance use since the pandemic began (OR = 9.90, 95% CI = 4.27-23.06). Participants with the highest exposure to cable news and low knowledge of COVID-19 were over 11 times more likely to experience an increase in substance use (OR = 11.64, 95% CI = 4.01-24.45). CONCLUSION: Based on our findings, we recommend that media organizations should aim to reduce uncertainty and also provide positive coverage to counter the negative information associated with pandemics.

GPS-based built environment measures associated with adult physical activity.

Studies often rely on home locations to access built environment (BE) influences on physical activity (PA). We use GPS and accelerometer data collected for 288 individuals over a two-week period to examine eight GPS-derived BE characteristics and moderate-to-vigorous PA (MVPA) and light-to-moderate-vigorous PA (LMVPA). NDVI, parks, blue space, pedestrian-orientated intersections, and population density were associated with increased odds of LMVPA and MVPA, while traffic air pollution and noise were associated with decreased odds of LMVPA and MVPA. Associations varied by population density and when accounting for multiple BE measures. These findings provide further information on where individuals choose to be physically active.

Access to medication-assisted treatment in the United States: Comparison of travel time to opioid treatment programs and office-based buprenorphine treatment.

OBJECTIVES: Disparities in access to medication-assisted treatment are a major problem. This study estimated and compared drive time to the nearest opioid treatment program (OTP) and office-based buprenorphine treatment (OBBT) across the urban-rural continuum in the U.S. METHODS: Drive time was calculated between the longitude and latitude of population weighted block group centroids and the longitude and latitude of the nearest OTP and OBBT. Rural-Urban Commuting Area (RUCA) codes were used for defining rurality. The Integrated Nested Laplace Approximation approach was used for statistical analysis. RESULTS: The mean travel time to the nearest OBBT compared to OTP decreased by 7.18 min (95 % CI = 7.23-7.14) in metropolitan cores, 36.63 min (95 % CI = 37.12-36.15) in micropolitan cores, 38.84 min (95 % CI = 39.57-38.10) in small town cores, and 40.16 min (95 % CI = 40.81-39.50) in rural areas. Additionally, travel burden to the nearest OTP would be more than 60 min for 13,526,605 people and more than 90 min for 5,371,852 people. The travel burden to the nearest OBBT would be more than 60 min for 845,991 people and more than 90 min for 149,297 people. CONCLUSIONS: The mean drive time to the closest OBBT was significantly smaller than the mean drive time to the closest OTP. Analysis of barriers to access is necessary to devising creative initiatives to improve access to critical opioid use disorder treatment services.