Rienna G. Russo

Background: Limited evidence is available from randomized trials to guide clinical decision making for cardiovascular disease (CVD) prevention with statins among women with breast cancer. We leveraged real-world data to estimate the effect of statin therapy vs usual care on the 5-year risk of CVD among breast cancer survivors. Methods: We sequentially emulated target trials using the National Cancer Institute–Kaiser Permanente Breast Cancer Survivors Cohort. Women aged 40-84 years, diagnosed with stages 0-III breast cancer from 1993 to 2022, without CVD, no statins in the past 6 months, and low-density lipoprotein cholesterol from 100 to 160 mg/dL were included. The outcome was CVD (ischemic heart disease, stroke, and cardiomyopathy/heart failure). We compared statin therapy to usual care (no statins unless indicated) in intention-to-treat and per-protocol analyses. Results: Statin initiators were more likely to be older with a higher prevalence of cardiovascular comorbidities. In the intention-to-treat analysis, the 5-year risk difference was 0.3% (95% CI = −0.9 to 1.5), and risk ratio was 1.04 (95% CI = 0.86 to 1.25) for statin vs usual care. At 5 years, the proportion adherent to their initial strategy was 48% for statin and 24% for usual care. In the per-protocol analysis, the risk difference was −0.9% (95% CI = −2.9 to 2.2) and the risk ratio was 0.85 (95% CI = 0.51 to 1.36) for statin vs usual care. Conclusions: Our findings suggest that statin therapy may reduce the risk of CVD for breast cancer survivors, but the estimates are too imprecise for specific recommendations. Future research is needed to understand reasons for statin discontinuation, and opportunities to encourage adherence in this high-risk population.

The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack—Lipid-Lowering Trial (ALLHAT-LLT) was a pragmatic randomized trial conducted in 513 clinical centers across North America from 1994 to 2002. ALLHAT-LLT, which used standard of care (usual care) as the control treatment, did not find an effect of assignment to pravastatin on all-cause death. We aimed to use the trial data to estimate the effect of adhering to the assigned treatment, that is, the per-protocol effect. Moderately hypercholesterolemic (low-density lipoprotein cholesterol 100-189 mg/dL), hypertensive participants ≥55 years old were included and randomized to pravastatin (40 mg/day unless contraindicated) or usual care (lipid-lowering treatment discouraged unless clinically indicated). Of 10 355 individuals randomized, we included 9741 with complete baseline data. One-third of individuals in the pravastatin arm were non-adherent to the assigned treatment strategy at year 5. After adjusting for factors related to adherence, the 5 year risk difference comparing pravastatin to usual care was −3.0% (−4.9%, −1.3%), and the risk ratio was 0.79 (0.68, 0.91) for death. Findings were consistent across different definitions of treatment strategies. Our results suggest that the use of pravastatin under full adherence was protective against death, even if assignment to pravastatin was not clearly protective.

Background: Aspirin, an effective, low‐cost pharmaceutical, can significantly reduce mortality if used promptly after acute myocardial infarction (AMI). However, many AMI survivors do not receive aspirin within a few hours of symptom onset. Our aim was to quantify the mortality benefit of self‐administering aspirin at chest pain onset, considering the increased risk of bleeding and costs associated with widespread use. Methods and Results: We developed a population simulation model to determine the impact of self‐administering 325 mg aspirin within 4 hours of severe chest pain onset. We created a synthetic cohort of adults ≥ 40 years old experiencing severe chest pain using 2019 US population estimates, AMI incidence, and sensitivity/specificity of chest pain for AMI. The number of annual deaths delayed was estimated using evidence from a large, randomized trial. We also estimated the years of life saved (YOLS), costs, and cost per YOLS. Initiating aspirin within 4 hours of severe chest pain onset delayed 13 016 (95% CI, 11 643–14 574) deaths annually, after accounting for deaths due to bleeding (963; 926–1003). This translated to an estimated 166 309 YOLS (149391–185 505) at the cost of $643 235 (633 944–653 010) per year, leading to a cost‐effectiveness ratio of $3.70 (3.32–4.12) per YOLS. Conclusions: For <$4 per YOLS, self‐administration of aspirin within 4 hours of severe chest pain onset has the potential to save 13 000 lives per year in the US population. Benefits of reducing deaths post‐AMI outweighed the risk of bleeding deaths from aspirin 10 times over.

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.

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.

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.

Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention.

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.