Characterizing the neighborhood risk environment in multisite clinic-based cohort studies: A practical geocoding and data linkages protocol for protected health information.

BackgroundMaintaining patient privacy when geocoding and linking residential address information with neighborhood-level data can create challenges during research. Challenges may arise when study staff have limited training in geocoding and linking data, or when non-study staff with appropriate expertise have limited availability, are unfamiliar with a study's population or objectives, or are not affordable for the study team. Opportunities for data breaches may also arise when working with non-study staff who are not on-site. We detail a free, user-friendly protocol for constructing indices of the neighborhood risk environment during multisite, clinic-based cohort studies that rely on participants' protected health information. This protocol can be implemented by study staff who do not have prior training in Geographic Information Systems (GIS) and can help minimize the operational costs of integrating geographic data into public health projects.MethodsThis protocol demonstrates how to: (1) securely geocode patients' residential addresses in a clinic setting and match geocoded addresses to census tracts using Geographic Information System software (Esri, Redlands, CA); (2) ascertain contextual variables of the risk environment from the American Community Survey and ArcGIS Business Analyst (Esri, Redlands, CA); (3) use geoidentifiers to link neighborhood risk data to census tracts containing geocoded addresses; and (4) assign randomly generated identifiers to census tracts and strip census tracts of their geoidentifiers to maintain patient confidentiality.ResultsCompletion of this protocol generates three neighborhood risk indices (i.e., Neighborhood Disadvantage Index, Murder Rate Index, and Assault Rate Index) for patients' coded census tract locations.ConclusionsThis protocol can be used by research personnel without prior GIS experience to easily create objective indices of the neighborhood risk environment while upholding patient confidentiality. Future studies can adapt this protocol to fit their specific patient populations and analytic objectives

Characterizing the neighborhood risk environment in multisite clinic-based cohort studies: A practical geocoding and data linkages protocol for protected health information

Background Maintaining patient privacy when geocoding and linking residential address information with neighborhood-level data can create challenges during research. Challenges may arise when study staff have limited training in geocoding and linking data, or when non-study staff with appropriate expertise have limited availability, are unfamiliar with a study’s population or objectives, or are not affordable for the study team. Opportunities for data breaches may also arise when working with non-study staff who are not on-site. We detail a free, user-friendly protocol for constructing indices of the neighborhood risk environment during multisite, clinic-based cohort studies that rely on participants’ protected health information. This protocol can be implemented by study staff who do not have prior training in Geographic Information Systems (GIS) and can help minimize the operational costs of integrating geographic data into public health projects. Methods This protocol demonstrates how to: (1) securely geocode patients’ residential addresses in a clinic setting and match geocoded addresses to census tracts using Geographic Information System software (Esri, Redlands, CA); (2) ascertain contextual variables of the risk environment from the American Community Survey and ArcGIS Business Analyst (Esri, Redlands, CA); (3) use geoidentifiers to link neighborhood risk data to census tracts containing geocoded addresses; and (4) assign randomly generated identifiers to census tracts and strip census tracts of their geoidentifiers to maintain patient confidentiality. Results Completion of this protocol generates three neighborhood risk indices (i.e., Neighborhood Disadvantage Index, Murder Rate Index, and Assault Rate Index) for patients’ coded census tract locations. Conclusions This protocol can be used by research personnel without prior GIS experience to easily create objective indices of the neighborhood risk environment while upholding patient confidentiality. Future studies can adapt this protocol to fit their specific patient populations and analytic objectives

Examining neighborhood and interpersonal norms and social support on fruit and vegetable intake in low-income communities

Abstract Background We examined whether neighborhood-, friend-, and family- norms and social support for consumption and purchase of fruits and vegetables (F&V) were associated with F&V intake among low-income residents in subsidized housing communities. We examined baseline data from a study ancillary to the Live Well/Viva Bien intervention. Participants included 290 residents in four low-income subsidized housing sites who were ≥ 18 years of age, English and/or Spanish speaking, and without medical conditions that prevented consumption of F&V. Methods Linear regression models examined associations of norms and social support with F&V intake after adjustments for sociodemographic characteristics. Results In the analysis, neighborhood social support for F&V was associated with a 0.31 cup increase in F&V intake (95% CI = 0.05, 0.57). The family norm for eating F&V and family social support for eating F&V were associated with a 0.32 cup (95% CI = 0.13, 0.52) and 0.42 cup (95% CI = 0.19, 0.64) increase in F&V intake, respectively. Conclusions To our knowledge, no other studies have examined neighborhood, family, and peer norms and social support simultaneously and in relation to F&V intake. These findings may inform neighborhood interventions and community-level policies to reduce neighborhood disparities in F&V consumption

Resilience and HIV: a review of the definition and study of resilience

We use a socioecological model of health to define resilience, review the definition and study of resilience among persons living with human immunodeficiency virus (PLWH) in the existing peer-reviewed literature, and discuss the strengths and limitations of how resilience is defined and studied in HIV research. We conducted a review of resilience research for HIV-related behaviors/outcomes of antiretroviral therapy (ART) adherence, clinic attendance, CD4 cell count, viral load, viral suppression, and/or immune functioning among PLWH. We performed searches using PubMed, PsycINFO and Google Scholar databases. The initial search generated 14,296 articles across the three databases, but based on our screening of these articles and inclusion criteria, n = 54 articles were included for review. The majority of HIV resilience research defines resilience only at the individual (i.e., psychological) level or studies individual and limited interpersonal resilience (e.g., social support). Furthermore, the preponderance of HIV resilience research uses general measures of resilience; these measures have not been developed with or tailored to the needs of PLWH. Our review suggests that a socioecological model of health approach can more fully represent the construct of resilience. Furthermore, measures specific to PLWH that capture individual, interpersonal, and neighborhood resilience are needed

Macro-enabled excel file.

Macro-enabled Excel file that can be used to (1) Link census tracts containing patient geocoded addresses to indicators of neighborhood crime and socioeconomic disadvantage using the census tract geoidentifier, and (2) Assign randomly generated identification numbers to census tracts and strip them of geoidentifiers to maintain patient confidentiality. (XLSM)</p

A Concept Mapping Study to Understand Multilevel Resilience Resources Among African American/Black Adults Living with HIV in the Southern United States

Resilience may help people living with HIV (PLWH) overcome adversities to disease management. This study identifies multilevel resilience resources among African American/Black (AA/B) PLWH and examines whether resilience resources differ by demographics and neighborhood risk environments. We recruited participants and conducted concept mapping at two clinics in the southeastern United States. Concept Mapping incorporates qualitative and quantitative methods to represent participant-generated concepts via two-dimensional maps. Eligible participants had to attend ≥ 75% of their scheduled clinic appointments and did not have ≥ 2 consecutive detectable HIV-1 viral load measurements in the past 2 years. Of the 85 AA/B PLWH who were invited, forty-eight participated. Twelve resilience resource clusters emerged-five individual, two interpersonal, two organizational/policy and three neighborhood level clusters. There were strong correlations in cluster ratings for demographic and neighborhood risk environment comparison groups (r ≥ 0.89). These findings could inform development of theories, measures and interventions for AA/B PLWH

Development of Long and Short Forms of the Multilevel Resilience Resource Measure for African American/Black Adults Living with HIV

Understanding resilience in relation to HIV-related outcomes may help address racial/ethnic disparities, however, significant gaps in its measurement preclude in-depth study. Thus, this research aims to develop and evaluate the psychometric properties of long and short forms of the Multilevel Resilience Resource Measure for African American/Black Adults Living with HIV. To develop the items, we conducted a mixed methods study ( N  = 48) and reviewed published resilience measures. We completed content validity index analyses to ensure the items reflected the resilience construct. Next, we conducted 20 cognitive interviews and a field survey ( N  = 400). The long and short forms demonstrated acceptable to excellent psychometric properties based on factorial validity, internal consistency and convergent validity and on measurement invariance (conducted for the short form only). These measures provide a comprehensive framework to examine resilience and HIV-related outcomes and can inform resilience-building interventions to reduce racial and ethnic health disparities

Examining relationships between perceived neighborhood social cohesion and ideal cardiovascular health and whether psychosocial stressors modify observed relationships among JHS, MESA, and MASALA participants

BackgroundPsychosocial stressors increase the risks for cardiovascular disease across diverse populations. However, neighborhood level resilience resources may protect against poor cardiovascular health (CVH). This study used data from three CVH cohorts to examine longitudinally the associations of a resilience resource, perceived neighborhood social cohesion (hereafter referred to as neighborhood social cohesion), with the American Heart Association's Life's Simple 7 (LS7), and whether psychosocial stressors modify observed relationships.MethodsWe examined neighborhood social cohesion (measured in tertiles) and LS7 in the Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, and Mediators of Atherosclerosis in South Asians Living in America study. We used repeated-measures, modified Poisson regression models to estimate the relationship between neighborhood social cohesion and LS7 (primary analysis, n = 6,086) and four biological metrics (body mass index, blood pressure, cholesterol, blood glucose; secondary analysis, n = 7,291). We assessed effect measure modification by each psychosocial stressor (e.g., low educational attainment, discrimination).ResultsIn primary analyses, adjusted prevalence ratios (aPR) and 95% confidence intervals (CIs) for ideal/intermediate versus poor CVH among high or medium (versus low) neighborhood social cohesion were 1.01 (0.97-1.05) and 1.02 (0.98-1.06), respectively. The psychosocial stressors, low education and discrimination, functioned as effect modifiers. Secondary analyses showed similar findings. Also, in the secondary analyses, there was evidence for effect modification by income.ConclusionWe did not find much support for an association between neighborhood social cohesion and LS7, but did find evidence of effect modification. Some of the effect modification results operated in unexpected directions. Future studies should examine neighborhood social cohesion more comprehensively and assess for effect modification by psychosocial stressors