Stakeholder Perspectives on the Impact of COVID-19 on the Implementation of a Community-Clinic Linkage Model in New York City.

Community-clinical linkage models (CCLM) have the potential to reduce health disparities, especially in underserved communities; however, the COVID-19 pandemic drastically impacted their implementation. This paper explores the impact of the pandemic on the implementation of CCLM intervention led by community health workers (CHWs) to address diabetes disparities among South Asian patients in New York City. Guided by the Consolidated Framework for Implementation Research (CFIR), 22 stakeholders were interviewed: 7 primary care providers, 7 CHWs, 5 community-based organization (CBO) representatives, and 3 research staff. Semi-structured interviews were conducted; interviews were audio-recorded and transcribed. CFIR constructs guided the identification of barriers and adaptations made across several dimensions of the study's implementation context. We also explored stakeholder-identified adaptations used to mitigate the challenges in the intervention delivery using the Model for Adaptation Design and Impact (MADI) framework. (1) Communication and engagement refers to how stakeholders communicated with participants during the intervention period, including difficulties experienced staying connected with intervention activities during the lockdown. The study team and CHWs developed simple, plain-language guides designed to enhance digital literacy. (2) Intervention/research process describes intervention characteristics and challenges stakeholders faced in implementing components of the intervention during the lockdown. CHWs modified the health curriculum materials delivered remotely to support engagement in the intervention and health promotion. (3) community and implementation context pertains to the social and economic consequences of the lockdown and their effect on intervention implementation. CHWs and CBOs enhanced efforts to provide emotional/mental health support and connected community members to resources to address social needs. Study findings articulate a repository of recommendations for the adaptation of community-delivered programs in under-served communities during a time of public health crises.

Examining Changes in Sleep Duration Associated with the Onset of the COVID-19 Pandemic: Who is Sleeping and Who is Not?

The COVID-19 pandemic has resulted in social isolation and reports of insomnia. However, reports of changes in sleep duration and associated factors are few. To determine the impact of COVID-19 on changes in sleep behavior, data were analyzed from an online survey of adults recruited via social media that included questions asking whether the respondent slept less or more after the onset of the pandemic as well as self-reported sociodemographic and occupational information; beliefs about COVID-19; and responses pertaining to loneliness, anxiety, and depression. There were 5,175 respondents; 53.9% had a change in sleep duration.17.1% slept less and 36.7% slept more. Sleeping more was related to greater education, being single/divorced/separated, unemployed or a student. Being retired, divorced/separated or a homemaker, and living in the Mountain or Central time zones were associated with less sleep. Beliefs that COVID-19 would result in personal adverse consequences was associated with both more and less sleep. However, the strongest associations for both more and less sleep were seen with depression, anxiety, and loneliness. In summary, changes in sleep duration since the start of the COVID-19 pandemic were highly prevalent among social media users and were associated with several sociodemographic factors and beliefs that COVID-19 would have adverse personal impacts. However, the strongest associations occurred with worse mental health suggesting that improvements may occur with better sleep.Supplemental data for this article is available online at https://doi.org/10.1080/08964289.2021.2002800 .

Socioeconomic predictors of COVID-19-related health disparities among United States workers: A structural equation modeling study

The COVID-19 pandemic has disproportionately impacted the physical and mental health, and the economic stability, of specific population subgroups in different ways, deepening existing disparities. Essential workers have faced the greatest risk of exposure to COVID-19;women have been burdened by caretaking responsibilities;and rural residents have experienced healthcare access barriers. Each of these factors did not occur on their own. While most research has so far focused on individual factors related to COVID-19 disparities, few have explored the complex relationships between the multiple components of COVID-19 vulnerabilities. Using structural equation modeling on a sample of United States (U.S.) workers (N = 2800), we aimed to 1) identify factor clusters that make up specific COVID-19 vulnerabilities, and 2) explore how these vulnerabilities affected specific subgroups, specifically essential workers, women and rural residents. We identified 3 COVID-19 vulnerabilities: financial, mental health, and healthcare access;9 out of 10 respondents experienced one;15% reported all three. Essential workers [standardized coefficient (β) = 0.23;unstandardized coefficient (B) = 0.21, 95% CI = 0.17, 0.24] and rural residents (β = 0.13;B = 0.12, 95% CI = 0.09, 0.16) experienced more financial vulnerability than non-essential workers and non-rural residents, respectively. Women (β = 0.22;B = 0.65, 95% CI = 0.65, 0.74) experienced worse mental health than men;whereas essential workers reported better mental health (β = -0.08;B = -0.25, 95% CI = -0.38, -0.13) than other workers. Rural residents (β = 0.09;B = 0.15, 95% CI = 0.07, 0.24) experienced more healthcare access barriers than non-rural residents. Findings highlight how interrelated financial, mental health, and healthcare access vulnerabilities contribute to the disproportionate COVID-19-related burden among U.S. workers. Policies to secure employment conditions, including fixed income and paid sick leave, are urgently needed to mitigate pandemic-associated disparities.

Online Grocery Shopping Behaviors and Attitudes Among Asian Americans.

How online grocery shopping behaviors differ among Asian American (AA) ethnic subgroups and acculturation level is unknown. From June 9-15, 2020, we administered an online survey to a nationally-derived nonprobability sample of 2,895 AA adults, including 1,737 East, 570 South, and 587 Southeast Asian adults, assessing online grocery shopping (yes/no, frequency, reasons). We used logistic regression to compare responses by subgroup and acculturation score, controlling for sociodemographics. Thirty-percent of participants reported shopping online for groceries in a typical month, with a higher percentage among South (45%) versus East Asian adults (23%). Participants with low (vs. high) acculturation scores were more likely to report a lack of special foods (OR = 0.7; 95% CI: 0.5-0.98) and poor food quality (OR = 0.6; 95% CI: 0.4-0.7) as preventing them from shopping online. Online grocery shopping has the capacity to address inequities in health, potentially via culturally-tailored programs designed for less-acculturated AA adults.

What predicts people's belief in COVID-19 misinformation? A retrospective study using a nationwide online survey among adults residing in the United States.

BACKGROUND: Tackling infodemics with flooding misinformation is key to managing the COVID-19 pandemic. Yet only a few studies have attempted to understand the characteristics of the people who believe in misinformation. METHODS: Data was used from an online survey that was administered in April 2020 to 6518 English-speaking adult participants in the United States. We created binary variables to represent four misinformation categories related to COVID-19: general COVID-19-related, vaccine/anti-vaccine, COVID-19 as an act of bioterrorism, and mode of transmission. Using binary logistic regression and the LASSO regularization, we then identified the important predictors of belief in each type of misinformation. Nested vector bootstrapping approach was used to estimate the standard error of the LASSO coefficients. RESULTS: About 30% of our sample reported believing in at least one type of COVID-19-related misinformation. Belief in one type of misinformation was not strongly associated with belief in other types. We also identified 58 demographic and socioeconomic factors that predicted people's susceptibility to at least one type of COVID-19 misinformation. Different groups, characterized by distinct sets of predictors, were susceptible to different types of misinformation. There were 25 predictors for general COVID-19 misinformation, 42 for COVID-19 vaccine, 36 for COVID-19 as an act of bioterrorism, and 27 for mode of COVID-transmission. CONCLUSION: Our findings confirm the existence of groups with unique characteristics that believe in different types of COVID-19 misinformation. Findings are readily applicable by policymakers to inform careful targeting of misinformation mitigation strategies.

Giving Families a Voice for Equitable Healthy Food Access in the Wake of Online Grocery Shopping.

Understanding the views of families from low-income backgrounds about inequities in healthy food access and grocery purchase is critical to food access policies. This study explored perspectives of families eligible for the Supplemental Nutrition Assistance Program (SNAP) on healthy food access in physical and online grocery environments. The qualitative design used purposive sampling of 44 primary household food purchasers with children (aged ≤ 8), between November 2020-March 2021, through 11 online focus groups and 5 in-depth interviews. Grounded theory was used to identify community-level perceived inequities, including influences of COVID-19 pandemic, SNAP and online grocery services. The most salient perceived causes of inequitable food access were neighborhood resource deficiencies and public transportation limitations. Rural communities, people with disabilities, older adults, racially and ethnically diverse groups were perceived to be disproportionately impacted by food inequities, which were exacerbated by the pandemic. The ability to use SNAP benefits to buy foods online facilitated healthy food access. Delivery fees and lack of control over food selection were barriers. Barriers to healthy food access aggravated by SNAP included social stigma, inability to acquire cooked meals, and inadequate amount of monthly funds. Findings provide a foundation for policy redesign to promote equitable healthy food systems.

Employment conditions as barriers to the adoption of COVID-19 mitigation measures: how the COVID-19 pandemic may be deepening health disparities among low-income earners and essential workers in the United States.

BACKGROUND: The COVID-19 pandemic has disproportionately impacted economically-disadvantaged populations in the United States (US). Precarious employment conditions may contribute to these disparities by impeding workers in such conditions from adopting COVID-19 mitigation measures to reduce infection risk. This study investigated the relationship between employment and economic conditions and the adoption of COVID-19 protective behaviors among US workers during the initial phase of the COVID-19 pandemic. METHODS: Employing a social media advertisement campaign, an online, self-administered survey was used to collect data from 2,845 working adults in April 2020. Hierarchical generalized linear models were performed to assess the differences in engagement with recommended protective behaviors based on employment and economic conditions, while controlling for knowledge and perceived threat of COVID-19, as would be predicted by the Health Belief Model (HBM). RESULTS: Essential workers had more precarious employment and economic conditions than non-essential workers: 67% had variable income; 30% did not have paid sick leave; 42% had lost income due to COVID-19, and 15% were food insecure. The adoption of protective behaviors was high in the sample: 77% of participants avoided leaving home, and 93% increased hand hygiene. Consistent with the HBM, COVID-19 knowledge scores and perceived threat were positively associated with engaging in all protective behaviors. However, after controlling for these, essential workers were 60% and 70% less likely than non-essential workers, who by the nature of their jobs cannot stay at home, to stay at home and increase hand hygiene, respectively. Similarly, participants who could not afford to quarantine were 50% less likely to avoid leaving home (AOR: 0.5; 95% CI: 0.4, 0.6) than those who could, whereas there were no significant differences concerning hand hygiene. CONCLUSIONS: Our findings are consistent with the accumulating evidence that the employment conditions of essential workers and other low-income earners are precarious, that they have experienced disproportionately higher rates of income loss during the initial phase of the COVID-19 pandemic and face significant barriers to adopting protective measures. Our findings underscore the importance and need of policy responses focusing on expanding social protection and benefits to prevent the further deepening of existing health disparities in the US.

Socioeconomic predictors of COVID-19-related health disparities among United States workers: A structural equation modeling study.

The COVID-19 pandemic has disproportionately impacted the physical and mental health, and the economic stability, of specific population subgroups in different ways, deepening existing disparities. Essential workers have faced the greatest risk of exposure to COVID-19; women have been burdened by caretaking responsibilities; and rural residents have experienced healthcare access barriers. Each of these factors did not occur on their own. While most research has so far focused on individual factors related to COVID-19 disparities, few have explored the complex relationships between the multiple components of COVID-19 vulnerabilities. Using structural equation modeling on a sample of United States (U.S.) workers (N = 2800), we aimed to 1) identify factor clusters that make up specific COVID-19 vulnerabilities, and 2) explore how these vulnerabilities affected specific subgroups, specifically essential workers, women and rural residents. We identified 3 COVID-19 vulnerabilities: financial, mental health, and healthcare access; 9 out of 10 respondents experienced one; 15% reported all three. Essential workers [standardized coefficient (ß) = 0.23; unstandardized coefficient (B) = 0.21, 95% CI = 0.17, 0.24] and rural residents (ß = 0.13; B = 0.12, 95% CI = 0.09, 0.16) experienced more financial vulnerability than non-essential workers and non-rural residents, respectively. Women (ß = 0.22; B = 0.65, 95% CI = 0.65, 0.74) experienced worse mental health than men; whereas essential workers reported better mental health (ß = -0.08; B = -0.25, 95% CI = -0.38, -0.13) than other workers. Rural residents (ß = 0.09; B = 0.15, 95% CI = 0.07, 0.24) experienced more healthcare access barriers than non-rural residents. Findings highlight how interrelated financial, mental health, and healthcare access vulnerabilities contribute to the disproportionate COVID-19-related burden among U.S. workers. Policies to secure employment conditions, including fixed income and paid sick leave, are urgently needed to mitigate pandemic-associated disparities.

Assessing changes in the food retail environment during the COVID-19 pandemic: opportunities, challenges, and lessons learned.

BACKGROUND: COVID-19 mitigation strategies have had an untold effect on food retail stores and restaurants. Early evidence from New York City (NYC) indicated that these strategies, among decreased travel from China and increased fears of viral transmission and xenophobia, were leading to mass closures of businesses in Manhattan's Chinatown. The constantly evolving COVID -19 crisis has caused research design and methodology to fundamentally shift, requiring adaptable strategies to address emerging and existing public health problems such as food security that may result from closures of food outlets. OBJECTIVE: We describe innovative approaches used to evaluate changes to the food retail environment amidst the constraints of the pandemic in an urban center heavily burdened by COVID-19. Included are challenges faced, lessons learned and future opportunities. METHODS: First, we identified six diverse neighborhoods in NYC: two lower-resourced, two higher-resourced, and two Chinese ethnic enclaves. We then developed a census of food outlets in these six neighborhoods using state and local licensing databases. To ascertain the status (open vs. closed) of outlets pre-pandemic, we employed a manual web-scraping technique. We used a similar method to determine the status of outlets during the pandemic. Two independent online sources were required to confirm the status of outlets. If two sources could not confirm the status, we conducted phone call checks and/or in-person visits. RESULTS: The final baseline database included 2585 food outlets across six neighborhoods. Ascertaining the status of food outlets was more difficult in lower-resourced neighborhoods and Chinese ethnic enclaves compared to higher-resourced areas. Higher-resourced neighborhoods required fewer phone call and in-person checks for both restaurants and food retailers than other neighborhoods. CONCLUSIONS: Our multi-step data collection approach maximized safety and efficiency while minimizing cost and resources. Challenges in remote data collection varied by neighborhood and may reflect the different resources or social capital of the communities; understanding neighborhood-specific constraints prior to data collection may streamline the process.

Social Media Use and Misinformation Among Asian Americans During COVID-19.

Social media has been crucial for seeking and communicating COVID-19 information. However, social media has also promulgated misinformation, which is particularly concerning among Asian Americans who may rely on in-language information and utilize social media platforms to connect to Asia-based networks. There is limited literature examining social media use for COVID-19 information and the subsequent impact of misinformation on health behaviors among Asian Americans. This perspective reviews recent research, news, and gray literature to examine the dissemination of COVID-19 misinformation on social media platforms to Chinese, Korean, Vietnamese, and South Asian Americans. We discuss the linkage of COVID-19 misinformation to health behaviors, with emphasis on COVID-19 vaccine misinformation and vaccine decision-making in Asian American communities. We then discuss community- and research-driven responses to investigate misinformation during the pandemic. Lastly, we propose recommendations to mitigate misinformation and address the COVID-19 infodemic among Asian Americans.

COVID-19, Social Determinants of Health, and Opportunities for Preventing Cardiovascular Disease: A Conceptual Framework.

The COVID-19 pandemic has disrupted the social, economic, and health care systems in the United States and shined a spotlight on the burden of disease associated with social determinants of health (SDOH). Addressing SDOH, while a challenge, provides important opportunities to mitigate cardiovascular disease incidence, morbidity, and mortality. We present a conceptual framework to examine the differential effects of the COVID-19 pandemic on SDOH across demographically diverse populations, focusing on the short- and long-term development of cardiovascular disease, as well as future research opportunities for cardiovascular disease prevention. The COVID-19 pandemic exerted negative shifts in SDOH and cardiovascular risk factors (ie, smoking, body mass index, physical activity, dietary behavior, cholesterol, blood pressure, and blood sugar). For example, evidence suggests that unemployment and food insecurity have increased, whereas health care access and income have decreased; changes to SDOH have resulted in increases in loneliness and processed food consumption, as well as decreases in physical activity and hypertension management. We found that policy measures enacted to mitigate economic, social, and health issues inadequately protected populations. Low-income and racial and ethnic minority communities, historically underserved populations, were not only disproportionately adversely affected by the pandemic but also less likely to receive assistance, likely attributable in part to the deep structural inequities pervasive in our society. Effective and culturally appropriate interventions are needed to mitigate the negative health impacts of historical systems, policies, and programs that created and maintain structural racism, especially for immigrants, racial and ethnic minorities, and populations experiencing social disadvantage.

Impact of COVID-19-related knowledge on protective behaviors: The moderating role of primary sources of information.

This study assessed the modifying role of primary source of COVID-19 information in the association between knowledge and protective behaviors related to COVID-19 among adults living in the United States (US). Data was collected from 6,518 US adults through an online cross-sectional self-administered survey via social media platforms in April 2020. Linear regression was performed on COVID-19 knowledge and behavior scores, adjusted for sociodemographic factors. An interaction term between knowledge score and primary information source was included to observe effect modification by primary information source. Higher levels of knowledge were associated with increased self-reported engagement with protective behaviors against COVID-19. The primary information source significantly moderated the association between knowledge and behavior, and analyses of simple slopes revealed significant differences by primary information source. This study shows the important role of COVID-19 information sources in affecting people's engagement in recommended protective behaviors. Governments and health agencies should monitor the use of various information sources to effectively engage the public and translate knowledge into behavior change during an evolving public health crisis like COVID-19.

Food insecurity among households with children during the COVID-19 pandemic: results from a study among social media users across the United States.

BACKGROUND: In the United States, approximately 11% of households were food insecure prior to the COVID-19 pandemic. The present study aims to describe the prevalence of food insecurity among adults and households with children living in the United States during the pandemic. METHODS: This study utilized social media as a recruitment platform to administer an original online survey on demographics and COVID-related food insecurity. The survey was disseminated through an advertisement campaign on Facebook and affiliated platforms. Food insecurity was assessed with a validated six-item United States Department of Agriculture (USDA) Household Food Security Survey Module, which was used to create a six-point numerical food security score, where a higher score indicates lower food security. Individual-level participant demographic information was also collected. Logistic regressions (low/very-low compared with high/marginal food security) were performed to generate adjusted odds ratios (AOR) and 95%CIs for food insecurity and select demographic characteristics. RESULTS: Advertisements reached 250,701 individuals and resulted in 5,606 complete surveys. Overall, 14.7% of participants self-identified as having low or very low food security in their households, with higher prevalence (17.5%) among households with children. Unemployment (AOR:1.76, 95%CI:1.09-2.80), high school or lower education (AOR:2.25, 95%CI:1.29-3.90), and low income (AOR[$30,000-$50,000]:5.87, 95%CI:3.35-10.37; AOR[< $30,000]:10.61, 95%CI:5.50-20.80) were associated with higher odds of food insecurity in multivariable models among households with children (and the whole sample). CONCLUSIONS: These data indicate exacerbation of food insecurity during the pandemic. The study will be instrumental in guiding additional research and time-sensitive interventions targeted towards vulnerable food insecure subgroups.

Contrasting the experiences for high- and low-income Asian Americans during COVID-19.

There is a lack of quantitative research examining how the pandemic has affected individuals at different income levels. The Asian American population has the highest level of income inequality and serves as an excellent case study for examining differences in experience between income groups. A non-probability sample of 3084 Asian American adults living in the US was surveyed in June 2020, examining health-related behaviors and outcomes. Descriptive analyses and chi-squared statistics were conducted to identify differences in income groups (low, medium, high) among Asian Americans across regional subgroups (East, South, Southeast, Multiethnic) and disaggregated ethnicities (Chinese, Asian Indian, Japanese, and Filipino). In bivariable analyses, a significantly (p < 0.05) greater percentage of high-income individuals during the pandemic reported having enough money to buy the food they needed, a away to get to the store for food, and reported stores where they get food had everything they needed. High-income Chinese, Japanese, and Filipino individual also noted that, since the COVID-19 crisis, they are now working partially or fully from home. In the total sample, multivariable adjusted logistic regressions revealed medium- and low-income individuals to have low odds of working partially or fully from home (AOR:0.55, 95%CI:0.42-0.72), higher odds of not having enough money to buy the food they needed (AOR:3.54, 95%CI:1.43-11.81), and higher odds of eating less (AOR:1.58, 95%CI:1.14-2.22). These results highlight the importance of considering income distribution when characterizing disparities in health behaviors within racial/ethnic minority groups and underscore the need to bolster the infrastructure supporting low-income Asian Americans.

COVID-19 Leads to Dramatic Changes in the Food Retail Environment in New York City: May-July 2020.

A systematic assessment of the effect of COVID-19 on the food retail environment-an important determinant of health-has not been conducted. Our objective was to assess the impact of COVID-19 on closures of restaurants, food retail stores, and fresh produce vendors in New York City (NYC). We conducted a cross-sectional study following the peak of COVID-19 in six neighborhoods in NYC. Two Chinese ethnic neighborhoods and four higher/lower resourced comparison neighborhoods were selected a priori based on 14 sociodemographic indicators. The primary outcome was indefinite/temporary closures or absence of food businesses. Of 2720 food businesses identified, produce vendors and restaurants were more likely to close than food retail stores. A higher proportion of food businesses closed in Chinese ethnic neighborhoods vs. comparison neighborhoods. COVID-19 impacted food businesses in six NYC neighborhoods examined in this period, with the greatest effect observed for Chinese ethnic neighborhoods.

Knowledge, beliefs, mental health, substance use, and behaviors related to the COVID-19 pandemic among US adults: a national online survey.

Aim: Given the need for data to inform public health messaging to mitigate the COVID-19 pandemic, this national survey sought to assess the state of COVID-19-related knowledge, beliefs, mental health, substance use changes, and behaviors among a sample of U.S. adults. Subject and methods: In the period March 20-30, 2020, we collected data on COVID-19-related knowledge, awareness and adoption of preventive practices, depression and anxiety (Patient Health Questionnaire-4), stress (Impact of Event Scale-6), pessimism, and tobacco and alcohol use. Differences between age groups (18-39 years, 40-59 years and ≥ 60 years) were tested using Pearson's chi-squared tests or ANOVAs; associations between drinking and smoking and depression, anxiety, and stress were tested using adjusted logistic regression models. Results: Approximately half of the sample (N Total = 6391) were 50-69 years old and 58% were female. COVID-19 knowledge (mean = 12.0; SD = 1.2) and protective practice awareness (mean = 9.1; SD = 0.8) were high. Among respondents, 44% had a score consistent with depression and anxiety (PHQ-4 score ≥ 6), and 52% reported high stress scores (≥ median of 1.33). COVID-19-related anxiety and depression were associated with increased drinking (AOR = 1.79; 95% CI = 1.49, 2.15) and smoking (AOR = 2.17; 95% CI = 1.64, 2.88). High stress scores were also associated with increased drinking (AOR = 1.80; 95% CI = 1.49, 2.17, p < 0.001) and smoking (AOR = 1.75; 95% CI = 1.31, 2.33). Conclusions: In spite of high knowledge levels, important gaps were identified. High prevalence of poor mental health outcomes and associated increases in drinking and smoking warrant ongoing risk communications tailoring to effectively disseminate information and expanding psychosocial services, particularly via telehealth, to mitigate the negative mental health impact of COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-021-01564-4.

Regional and socioeconomic predictors of perceived ability to access coronavirus testing in the United States: results from a nationwide online COVID-19 survey.

PURPOSE: Access to COVID-19 testing remained a salient issue during the early months of the pandemic, therefore this study aimed to identify 1) regional and 2) socioeconomic predictors of perceived ability to access Coronavirus testing. METHODS: An online survey using social media-based advertising was conducted among U.S. adults in April 2020. Participants were asked whether they thought they could acquire a COVID-19 test, along with basic demographic, socioeconomic and geographic information. RESULTS: A total of 6,378 participants provided data on perceived access to COVID-19 testing. In adjusted analyses, we found higher income and possession of health insurance to be associated with perceived ability to access Coronavirus testing. Geographically, perceived access was highest (68%) in East South Central division and lowest (39%) in West North Central. Disparities in health insurance coverage did not directly correspond to disparities in perceived access to COVID-19 testing. CONCLUSIONS: Sex, geographic location, income, and insurance status were associated with perceived access to COVID-19 testing; interventions aimed at improving either access or awareness of measures taken to improve access are warranted. These findings from the pandemic's early months shed light on the importance of disaggregating perceived and true access to screening during such crises.

Evaluating Closures of Fresh Fruit and Vegetable Vendors During the COVID-19 Pandemic: Methodology and Preliminary Results Using Omnidirectional Street View Imagery.

BACKGROUND: The COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises. OBJECTIVE: This study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks. METHODS: In total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the "notes" feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent. RESULTS: Of the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps "notes" feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices. CONCLUSIONS: The methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

Implementing Hypertension Management Interventions in Immigrant Communities in the U.S.: a Narrative Review of Recent Developments and Suggestions for Programmatic Efforts.

PURPOSE OF REVIEW: To outline intervention efforts focused on reducing hypertension disparities in immigrant communities in the U.S. and to identify areas in the design, implementation, and evaluation of these interventions that warrant further exploration guided by an implementation science framework. RECENT FINDINGS: Studies examined (n = 11) included immigrant populations of African, Hispanic, and Asian origin. Men were underrepresented in most studies. Culturally tailored group-based educational sessions in religious or community spaces were common. Intervention agents included research assistants, registered nurses, community health workers, and faith-based organization volunteers. Community stakeholders were engaged in most studies, although most commonly for recruitment efforts. Surveys/interviews were used for intervention evaluation, and documentation of intervention activities and trainings was used to assess fidelity. Identified pathways for further intervention innovation included gender or migration-status-based targeting, diversifying intervention agents, enhancing mixed-method process evaluations, and tailoring to emerging needs during the COVID-19 pandemic.

Increased alcohol use during the COVID-19 pandemic: The effect of mental health and age in a cross-sectional sample of social media users in the U.S.

The COVID-19 pandemic has triggered a public health crisis of unprecedented scale. Increased alcohol use has been extensively documented during other crises, particularly among persons with anxiety and depression. Despite COVID-19's differential impact by age, the association of age, mental health and alcohol use during the pandemic has not been explored. This study aimed to examine whether age modified the association of anxiety and depressive symptoms with alcohol use during the COVID-19 pandemic. Two online surveys were administered to U.S. adult social media users in March and April 2020. Generalized linear models were conducted in 2020 among 5850 respondents (52.9% female; 22.0% aged 18-39 years, 47.0% aged 40-59 years, and 31.0% aged ≥60 years) to examine if age modified the association of anxiety and depression symptomatology and alcohol use. Overall, 29% of respondents reported increased alcohol use. Adjusted odds ratios of reporting increased alcohol use were 1.41 (95% CI = 1.20-1.66) among respondents with anxiety symptoms and 1.64 (95% CI = 1.21-2.23) among those with depressive symptoms compared to those without such symptoms. Whereas respondents aged 18-39 years had the highest probability of reporting increased alcohol use, the probability of older persons (40-59 and ≥60 years) reporting increased drinking was much greater among those with symptoms of anxiety and depression, compared to those without symptoms. These findings warrant age-differentiated public health messaging on the risks of excessive alcohol use and scale-up of substance use services for middle-aged and older adults with symptoms of depression and anxiety.