Faculty Bibliography

BackgroundCommunity health workers (CHW) can perform unique functions to facilitate the implementation of evidence-based interventions for infection-related cancer prevention and control, and alleviate minoritized and immigration-related disparities.PurposeWe describe the implementation evaluation of three CHW-delivered infection-related cancer programs focused on Asian American (AA) communities in New York City: 1) a H. pylori treatment adherence program for Chinese and Korean Americans; 2) a HPV screening program for Muslim Americans; and 3) a hepatitis B screening, linkage to care, and treatment program for AA and other priority communities.MethodsWe conducted semi-structured key informant interviews with multi-level stakeholders from the programs.ResultsLessons learned include the importance of: 1) sustaining engagement and buy-in from implementation partners; 2) prioritizing recipient- and deliverer-centeredness; 3) fostering program flexibility to accommodate multiple implementation settings and to meet dynamic community resources and priorities; and 4) understanding interoperability between the CHW-delivered intervention and the inner setting for effective program implementation.ConclusionsThese findings can inform other efforts to implement CHW-delivered community-clinical cancer programs for AA and other underserved communities to advance health equity.

Urban parks may promote health through physical activity, stress management, and social connectedness. However, poor-quality parks in disrepair are underutilized, limiting these benefits. This study evaluated the impact of a citywide park renovation program known as the Community Parks Initiative (CPI) on changes in park use patterns and park satisfaction among residents living in low-income New York City neighborhoods. Repeated cross-sectional surveys were administered to residents living near 31 parks undergoing CPI renovations (545 pre-renovation and 201 post-renovation respondents) and near 21 parks in socio-demographically matched control neighborhoods (345 pre-renovation and 129 post-renovation respondents). Surveys measured self-reported past-month park visits, typical park visit duration, and satisfaction with park quality and facilities. Using a difference-in-differences (DID) approach, generalized estimating equations were fit to compare changes over time in park use and satisfaction among residents living near parks receiving renovations compared to those living near control parks. Models were adjusted for age, body mass index, income, public housing, marital status, and children in household. Residents in neighborhoods receiving park renovations reported a larger increase in minutes spent at the park on weekdays [DID = 30.0 min (95% CI 10.3, 49.7)] and total minutes spent at the park in the last 30 days [DID = 466.3 min (95% CI 63.0, 869.6)] compared to controls. Residents of renovated park neighborhoods also reported larger increases in park satisfaction relative to residents of control neighborhoods, with the largest improvements in the percent of residents satisfied with overall park quality [DID = 38.4% (95% CI 25.2, 51.6)] and maintenance of grounds and facilities [DID = 40.9% (95% CI 27.7, 54.1)]. This study provides evidence that park renovations are an important urban planning strategy to support community health through increased park use and improved park perceptions.

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.

BACKGROUND:We conducted a cost analysis of implementing a randomized controlled trial that proved the effectiveness of a community health worker (CHW) facilitated weight loss intervention among South Asian patients with prediabetes receiving care at primary care practices in New York City. South Asians have a high prevalence of diabetes, but no study to date has evaluated the cost of implementing an evidence-based lifestyle intervention in this population. Cost estimates are necessary for an intervention's adoption and scale-up. METHODS:The first wave of the intervention was implemented in-person, followed by two waves implemented remotely during the COVID-19 pandemic. We estimated the implementation, intervention, and adaptation costs and the costs by each wave of implementation, by applying the Gold et al.'s economic framework and ERIC discrete implementation strategy compilation Costs were calculated from the perspective of a health care payer, public health agency, or health care system. The CHW intervention included group education sessions over six months. For each wave, we separately estimated the total cost, cost per practice, and cost when implemented at only one practice. Using the Bureau of Labor Statistics salary estimates, we calculated the national average (mean salary) and lower (25th percentile salary) and upper (75th percentile salary) bounds. RESULTS:The average total 6-month implementation costs over 3 waves, each targeting seven practices was $215,420 (range: $158,620-$257,020). Program staff salaries comprised > 93% of total costs. Adaptation cost was nearly 1/3 of start-up costs. On average, implementation at one practice would cost twice as much as the per-practice costs when implemented simultaneously at seven practices in a wave, due to spread of start-up costs across multiple sites. CONCLUSIONS:Staff salaries comprise most of the budget to implement such an intervention. It is most efficient for an agency to implement this intervention across several practices simultaneously. Decision-makers will need to evaluate relative costs and effectiveness of other options to achieve weight loss in a minority community with constrained resources. CLINICALTRIALS:GOV: This study was registered on June 15, 2017 at  https://www. CLINICALTRIALS:gov as NCT03188094. https://clinicaltrials.gov/ct2/show/NCT03188094 .

RATIONALE & OBJECTIVE/OBJECTIVE:Despite national efforts, the uptake of home dialysis (peritoneal dialysis or home hemodialysis) remains low. Characteristics of the built environment may differentially impact home dialysis use. STUDY DESIGN/METHODS:Retrospective cohort study (2010-2019). SETTING & PARTICIPANTS/METHODS:1,103,695 adults (aged≥18 years) initiating dialysis in the US Renal Data System. EXPOSURE/METHODS:We examined 3 built environment domains based on residential ZIP code: (1) medically underserved areas (MUAs), defined as neighborhoods with limited primary care access; (2) distance to the nearest dialysis facility; and (3) distribution of housing characteristics (structure and overcrowding). OUTCOME/RESULTS:Uptake of home dialysis modalities at dialysis initiation. ANALYTICAL APPROACH/METHODS:We quantified associations between built environment characteristics and home dialysis initiation using multilevel logistic regression stratified by urbanicity type (urban, suburban, small-town, and rural). RESULTS:Among adults initiating dialysis, 40.8% lived in MUAs. Across ZIP codes, the mean percentage of overcrowded housing was 4.2% (SD, 4.7%), and the percentage of detached housing was 61.1% (SD, 21.1%); mean distance to the nearest dialysis facility was 5.5km (SD, 9.1km). Living in MUAs was associated with reduced home dialysis use only in urban (OR, 0.94; 95% CI, 0.91-0.96) and suburban (OR, 0.92; 95% CI, 0.89-0.94) areas. Similarly, housing overcrowding was associated with decreased home dialysis use only in urban (OR, 0.88; 95% CI, 0.86-0.89) and suburban (OR, 0.91; 95% CI, 0.90-0.93) areas. Longer distance to a dialysis facility was the most salient neighborhood factor associated with increased home dialysis use in small towns (OR, 1.14; 95% CI, 1.12-1.16) and rural areas (OR, 1.17; 95% CI, 1.15-1.19). LIMITATIONS/CONCLUSIONS:Housing characteristics were measured at the ZIP code level. CONCLUSIONS:Built environment characteristics associated with home dialysis uptake vary by urbanicity. Policies should address built environment barriers that are specific to urbanicity level. For example, increasing the frequency of dialysate delivery schedules could address housing space constraints in urban and suburban areas, and promoting home dialysis might be more effective for patients living far from dialysis centers in small-town and rural areas.

OBJECTIVE:To compare anonymized and non-anonymized approaches for imputing race and ethnicity in descriptive studies of chronic disease burden using electronic health record (EHR)-based datasets. STUDY SETTING AND DESIGN/METHODS:In this New York City-based study, we first conducted simulation analyses under different missing data mechanisms to assess the performance of Bayesian Improved Surname Geocoding (BISG), single imputation using neighborhood majority information, random forest imputation, and multiple imputation with chained equations (MICE). Imputation performance was measured using sensitivity, precision, and overall accuracy; agreement with self-reported race and ethnicity was measured with Cohen's kappa (κ). We then applied these methods to impute race and ethnicity in two EHR-based data sources and compared chronic disease burden (95% CIs) by race and ethnicity across imputation approaches. DATA SOURCES AND ANALYTIC SAMPLE/UNASSIGNED:Our data sources included EHR data from NYU Langone Health and the INSIGHT Clinical Research Network from 3/6/2016 to 3/7/2020 extracted for a parent study on older adults in NYC with multiple chronic conditions. PRINCIPAL FINDINGS/RESULTS: = 0.33). When these methods were applied to the NYU and INSIGHT cohorts, however, racial and ethnic distributions and chronic disease burden were consistent across all imputation methods. Slight improvements in the precision of estimates were observed under all imputation approaches compared to a complete case analysis. CONCLUSIONS:BISG imputation may provide a more accurate racial and ethnic classification than single or multiple imputation using anonymized covariates, particularly if the missing data mechanism is MNAR. Descriptive studies of disease burden may not be sensitive to methods for imputing missing data.

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:Black sexual minority men and Black transgender women (BSMM/BTW) experience disproportionate levels of HIV/STI-related risk factors as well as police harassment (PH). PH is linked to psychiatric risk and could play a role in substance use, sexual risk behavior, and HIV/STI risk. METHODS:We used data from the HIV Prevention Trials Network 061(HPTN 061) study to examine associations between PH and HIV/STI-related outcomes. Using PH exposure measured at baseline and 6-month study visits, we examined an ordinal exposure (PH reported at both visits, PH reported at either visit, versus PH reported at neither baseline nor 6 months) and a binary exposure of persistent PH reported at both visits (yes versus no). We estimate risk ratios (RR) for associations between PH and depression, use of alcohol and methamphetamine, multiple partnerships, condomless sex, and syphilis. RESULTS:Persistent PH (binary) was associated with a 20% or greater increase in the risk of depression (RR, 1.26 (1.07, 1.47)) and multiple partnerships (RR, 1.20 (1.05, 1.39)). There was evidence that ordinal PH was associated with elevated risk of alcohol use (RR, 1.17 (1.00, 1.36)); the point estimate for the association between persistent PH and alcohol use was similar but the imprecision was greater (RR, 1.16 (0.95, 1.42)). CONCLUSION/CONCLUSIONS:PH may influence not only mental health but also behavioral risks that contribute to HIV/STI among BSMM/BTW, highlighting the potential wide-ranging and downstream effects of PH on health. Further research is required to confirm associations and elucidate pathways through which PH may influence HIV/STI among BSMM/BTW.

OBJECTIVE:The Diabetes in Children, Adolescents, and Young Adults (DiCAYA) network seeks to create a nationwide electronic health record (EHR)-based diabetes surveillance system. This study aimed to develop a DiCAYA-wide EHR-based computable phenotype (CP) to identify prevalent cases of diabetes. RESEARCH DESIGN AND METHODS/METHODS:We conducted network-wide chart reviews of 2,134 youth (aged <18 years) and 2,466 young adults (aged 18 to <45 years) among people with possible diabetes. Within this population, we compared the performance of three alternative CPs, using diabetes diagnoses determined by chart review as the gold standard. CPs were evaluated based on their accuracy in identifying diabetes and its subtype. RESULTS:The final DiCAYA CP requires at least one diabetes diagnosis code from clinical encounters. Subsequently, diabetes type classification was based on the ratio of type 1 diabetes (T1D) or type 2 diabetes (T2D) diagnosis codes in the EHR. For both youth and young adults, the sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) in finding diabetes cases were >90%, except for the specificity and NPV in young adults, which were slightly lower at 83.8% and 80.6%, respectively. The final DiCAYA CP achieved >90% sensitivity, specificity, PPV, and NPV in classifying T1D, and demonstrated lower but robust performance in identifying T2D, consistently maintaining >80% across metrics. CONCLUSIONS:The DiCAYA CP effectively identifies overall diabetes and T1D in youth and young adults, though T2D misclassification in youth highlights areas for refinement. The simplicity of the DiCAYA CP enables broad deployment across diverse EHR systems for diabetes surveillance.

OBJECTIVE:This study examined associations between access to leisure-time physical activity (LTPA) facilities and parks and repeated measures of glycated hemoglobin (A1C) over time, using follow-up tests among United States Veterans with newly diagnosed type-2 diabetes (T2D). METHODS:Data were analyzed from 274,463 patients in the Veterans Administration Diabetes Risk cohort who were newly diagnosed with T2D between 2008 and 2018 and followed through 2023. Generalized estimating equations with a logit link function and binomial logistic regression were used to examine associations. RESULTS:Patients were on average 60.5 years of age, predominantly male (95.0 %) and white (66.9 %), and had an average of 11.7 A1C tests during the study follow-up period. In high- and low-density urban communities, a one-unit higher LTPA facility density score was associated with 1 % and 3 % greater likelihood of in-range A1C tests during follow-up, respectively, but no association was observed among patients living in suburban/small town and rural communities. Across community types, closer park distance was not associated with subsequent greater odds of in-range A1C tests. Unexpectedly, in low-density urban areas, the likelihood of in-range A1C tests was 1 % lower at farther park distances. CONCLUSIONS:These results suggest that broader access to LTPA facilities, but not park proximity, may contribute in small ways to maintaining glycemic control after T2D diagnosis in urban communities. Tailored interventions may be needed to promote patients' effective use of LTPA facilities and parks.