Faculty Bibliography

INTRODUCTION/BACKGROUND:Identifying strategies to mitigate the effects of secondhand smoke exposure is crucial for public health. Thus, we estimated the effect of a 2018 federal smoke-free housing (SFH) policy on adverse birth outcomes among New York City (NYC) public-housing residents. METHODS:We obtained data on all live births to NYC residents in NYC from 2013 to 2022, using the borough-block-lot of the birthing person's address to identify births to public-housing residents. We then estimated the effect of the SFH policy on risk of preterm birth or low birth weight among births to NYC public-housing residents using a linear-probability difference-in-differences estimator, weighted by inverse probability weights to increase the plausibility of the parallel-trends assumption. RESULTS:Our sample included 44 455 births to public-housing residents and 803 648 births to non-public-housing residents. Difference-in-difference analyses suggested the SFH policy did not affect risk of preterm birth (risk difference (RD) per 100: 0.1; 95% CI -0.6 to 0.9) or low birth weight (RD per 100: 0.3, 95% CI -0.4 to 1.0). Event-study analyses supported these findings and lent credibility to the parallel-trends assumption. CONCLUSIONS:We estimated no initial effects of a federal SFH policy on risk of preterm birth or low birth weight among births to NYC public-housing residents.

BACKGROUND/UNASSIGNED:Environmental epidemiology studies increasingly integrate "big" geospatial and health datasets to examine associations between environmental factors and health outcomes. Using such datasets - and linking between them - presents a number of complexities with regard to study design and analytic approaches. These complexities are often magnified with the integration of additional contextual data representing other neighborhood characteristics, including socioeconomic factors. Guidance regarding the design of environmental health studies that leverage "big" geospatial and health outcome data is limited and fragmented. OBJECTIVE/UNASSIGNED:Drawing on methodological literature and case studies, this commentary outlines common challenges related to geospatial and health data linkages, posing a series of guiding questions and considerations for investigators conducting environmental health studies, particularly analyses with an etiological focus. DISCUSSION/UNASSIGNED:Recommendations include: 1) using a target trial approach to guide causal analysis, 2) aligning measures with hypothesized causal mechanisms, 3) exploring opportunities to "groundtruth" and validate data, and 4) prioritizing interdisciplinary science. The goal of the commentary is to consolidate insights from multiple disciplines - including exposure science, epidemiology, and sociology - to provide a foundation for etiologic research focused on advancing environmental health for all populations. https://doi.org/10.1289/EHP15756.

INTRODUCTION/BACKGROUND:Effective July 2018, the U.S. Department of Housing and Urban Development issued a rule requiring all public housing authorities to implement smoke-free housing (SFH) policies in their developments. We examined the differential impacts of SFH policy on hospitalizations for myocardial infarction (MI) and stroke among adults aged ≥50 years old living in New York City (NYC) Housing Authority (NYCHA) versus a matched-comparison population in NYC. AIMS AND METHODS/OBJECTIVE:We identified census block groups (CBGs) comprised solely of 100% NYCHA units (N = 160) and compared NYCHA CBGs to a selected subset of CBGs from all CBGs with no NYCHA units (N = 5646). We employed propensity score matching on distributions of key CBG-level sociodemographic and housing covariates. We constructed incident rates per 1000 persons by aggregating 3-month "quarterly" counts of New York State all-payer hospitalization data from October 2015 to December 2022 and dividing by the population aged ≥50 in selected CBGs, ascertained from 2016 American Community Survey 5-year estimates. We selected a difference-in-differences (DID) analytic approach to examine pre- and post-policy differences in incident hospitalizations between the intervention and matched-comparison groups. RESULTS:Matching results indicated a balanced match for all covariates, with standardized mean differences <0.10. In DID analyses, we observed small declines in both MI (DID = -0.26, p = .02) and stroke (DID = -0.28, p = .06) hospitalization rates for NYCHA CBGs compared to non-NYCHA CBGs from pre-to post-54 months' policy. CONCLUSIONS:SFH policies in NYC were associated with small reductions in CVD-related hospitalizations among older adults living in housing subject to the policy. IMPLICATIONS/CONCLUSIONS:Housing remains a key focal setting for interventions to reduce SHS exposure and associated morbidities. Ongoing monitoring is warranted to understand the long-term impacts of SFH policies in public housing developments.

BACKGROUND:Disruption of ambulatory healthcare in New York City (NYC) during the COVID-19 pandemic was common, but the impact on the cardiometabolic health of vulnerable patient groups is unknown. Therefore, we estimated the effect of total care disruption (TCD) on blood pressure (BP) control among older NYC residents with hypertension and at least one other chronic condition, and examined whether neighborhood poverty moderated this impact. METHODS:From the INSIGHT Clinical Research Network, we identified NYC residents ≥50 years of age with hypertension and at least one other chronic condition. TCD was defined as no ambulatory or telehealth visit during the pandemic. We contrasted the change in prevalence of controlled BP (BP <140/90) before and after the pandemic among those with and without TCD via an inverse probability weighted (IPW) difference-in-difference regression model. RESULTS:Among 212,673 eligible individuals, mean age was 69.5 years (SD: 10.2 years) and 15.1% experienced TCD. BP control declined from 52.4% to 45.9% among those with TCD and from 53.6% to 48.9% among those without TCD. After IPW adjustment, a larger decline in BP control was noted among those with TCD (adjusted difference-in-difference = 1.13 percentage points (95% CI 0.32-1.94, p-value=0.0058)). There was no consistent difference in the relationship between TCD and post-pandemic BP control across neighborhood poverty levels. CONCLUSION/CONCLUSIONS:COVID-19-related TCD was associated with a modest decline in BP control among older adults with hypertension in NYC; this was not moderated by neighborhood poverty level.

PURPOSE OF REVIEW/OBJECTIVE:Despite emerging studies on neighborhood-level risk factors for chronic kidney disease (CKD), our understanding of the causal links between neighborhood characteristics and CKD is limited. In particular, there is a gap in identifying modifiable neighborhood factors, such as the built environment, in preventing CKD, that could be targets for feasible place-based interventions. RECENT FINDINGS/RESULTS:Most published studies on neighborhood factors and CKD have focused on a single social attribute, such as neighborhood disadvantage, while research on the role of the built environment is more nascent. Early studies on this topic have yielded inconsistent results, particularly regarding whether food deserts are an environmental risk factor for CKD onset. International studies have shown that walkable neighborhoods - characterized by features such as urban design, park access, and green spaces - can be protective against both the onset and progression of CKD. However, these findings are inconclusive and understudied in the context of United States, where neighborhood environments differ from those in other countries. SUMMARY/CONCLUSIONS:Future research on modifiable neighborhood factors and CKD using advanced study designs and population-representative datasets can yield stronger evidence on potential causal associations and suggest feasible place-based interventions as strategies for preventing CKD. As an example, we demonstrated the potential of electronic health record-based studies to advance research in this area.

In this policy brief, we explore several potential drivers of heterogeneity in policy outcomes that can be examined in tobacco control policy evaluations, expanding the evidence base to contribute to continued, equitable progress in reducing tobacco-related health outcomes. We discuss these factors in the context of a hypothetical evaluation of the impact of smoke-free laws on current smoking and quit attempts in the Tobacco Nation. Despite a similar policy environment within the Tobacco Nation, there is variation in the strength of smoke-free law coverage across states. This commentary considers how policy design and other contextual factors, including co-occurring policies, and differential impacts across subgroups, may influence policy-attributable outcomes across time and space.

In support of the environmental justice (EJ) movement, researchers, activists, and policymakers often use environmental data to document evidence of the unequal distribution of environmental burdens and benefits along lines of race, class, and other socioeconomic characteristics. Numerous limitations, such as spatial or temporal discontinuities, exist with commonly used data measurement techniques, which include ground monitoring and federal screening tools. Satellite data is well poised to address these gaps in EJ measurement and monitoring; however, little is known about how satellite data has advanced findings in EJ or can help to promote EJ through interventions. Thus, this scoping review aims to (1) explore trends in study design, topics, geographic scope, and satellite datasets used to research EJ, (2) synthesize findings from studies that use satellite data to characterize disparities and inequities across socio-demographic groups for various environmental categories, and (3) capture how satellite data are relevant to policy and real-world impact. Following PRISMA extension guidelines for scoping reviews, we retrieved 81 articles that applied satellite data for EJ research in the United States from 2000 to 2022. The majority of the studies leveraged the technical advantages of satellite data to identify socio-demographic disparities in exposure to environmental risk factors, such as air pollution, and access to environmental benefits, such as green space, at wider coverage and with greater precision than previously possible. These disparities in exposure and access are associated with health outcomes such as increased cardiovascular and respiratory diseases, mental illness, and mortality. Research using satellite data to illuminate EJ concerns can contribute to efforts to mitigate environmental inequalities and reduce health disparities. Satellite data for EJ research can therefore support targeted interventions or influence planning and policy changes, but significant work remains to facilitate the application of satellite data for policy and community impact.

Studies have recently begun to explore the potential long-term health impacts of homeownership policies implemented in the New Deal era. We investigated the association between assigned grades of lending risk by the Home Owners' Load Corporation (HOLC) maps from the 1930s and present-day prevalence of three cardiovascular risk factors (diabetes and obesity in 2020, and hypertension in 2019), estimated at the census tract level in the United States. To minimize potential confounding, we adjusted for sociodemographic data from the time period when HOLC maps were made. We calculated propensity scores (predicted probability of receiving a HOLC grade) and created a pseudo-population using inverse probability weighting. We then employed marginal structural models to estimate prevalence differences comparing A vs. B, B vs. C, and C vs. D HOLC grades. Adjusting only for regions, a less desirable HOLC grade was associated with higher estimated prevalence rates of present-day cardiovascular risk factors; however, most differences were no longer significant after applying propensity score methods. The one exception was that the prevalence of diabetes, hypertension, and obesity were all higher in C vs. B graded census tracts, while no differences were observed for C and D and A and B comparisons. These results contribute to a small body of evidence that suggests historical "yellowlining" (as C grade was in color yellow) may have had persistent impacts on neighborhood-level cardiovascular risk factors 80 years later.

During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies, and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS-CoV-2 testing services in New York City (NYC), as a core part of NYC's Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity, and timeliness of SARS-CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators, and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25 min away from free SARS-CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with the highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.