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      The intersection of neighborhood and race in urban adolescent health risk behaviors

      1 , 1 , 1
      Journal of Community Psychology
      Wiley

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          Abstract

          Aims

          Racial variability in associations of neighborhood socioeconomic disadvantage and neighborhood disorder with adolescent health risk behaviors remains under‐researched, which this study examined over 1 year among racially diverse adolescents.

          Methods

          High school students ( N = 345; 18% Asian, 44% Black, 16% Multiracial, 22% White) completed surveys assessing neighborhood socioeconomic disadvantage and neighborhood disorder, and health risk behaviors (lifetime alcohol, cannabis, and cigarette use, number of sexual partners) at baseline (Year 1) and 1‐year follow‐up (Year 2).

          Results

          Asian, Black, and Multiracial adolescents were more likely to endorse health risk behaviors in Year 2 compared to White adolescents living in similarly disadvantaged neighborhoods at Year 1. Associations of neighborhood disorder with health risk behavior did not differ by race.

          Conclusion

          Neighborhood socioeconomic disadvantage (but not neighborhood disorder) may predispose Asian, Black, and Multiracial adolescents to health risk behaviors. Findings may inform interventions to address racial disparities in adolescent health risk behaviors.

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          Most cited references91

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications.

            Link and Phelan (1995) developed the theory of fundamental causes to explain why the association between socioeconomic status (SES) and mortality has persisted despite radical changes in the diseases and risk factors that are presumed to explain it. They proposed that the enduring association results because SES embodies an array of resources, such as money, knowledge, prestige, power, and beneficial social connections that protect health no matter what mechanisms are relevant at any given time. In this article, we explicate the theory, review key findings, discuss refinements and limits to the theory, and discuss implications for health policies that might reduce health inequalities. We advocate policies that encourage medical and other health-promoting advances while at the same time breaking or weakening the link between these advances and socioeconomic resources. This can be accomplished either by reducing disparities in socioeconomic resources themselves or by developing interventions that, by their nature, are more equally distributed across SES groups.
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              Multilevel Modeling of Individual and Group Level Mediated Effects.

              This article combines procedures for single-level mediational analysis with multilevel modeling techniques in order to appropriately test mediational effects in clustered data. A simulation study compared the performance of these multilevel mediational models with that of single-level mediational models in clustered data with individual- or group-level initial independent variables, individual- or group-level mediators, and individual level outcomes. The standard errors of mediated effects from the multilevel solution were generally accurate, while those from the single-level procedure were downwardly biased, often by 20% or more. The multilevel advantage was greatest in those situations involving group-level variables, larger group sizes, and higher intraclass correlations in mediator and outcome variables. Multilevel mediational modeling methods were also applied to data from a preventive intervention designed to reduce intentions to use steroids among players on high school football teams. This example illustrates differences between single-level and multilevel mediational modeling in real-world clustered data and shows how the multilevel technique may lead to more accurate results.
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                Author and article information

                Contributors
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                Journal
                Journal of Community Psychology
                Journal Community Psychology
                Wiley
                0090-4392
                1520-6629
                May 2023
                November 26 2022
                May 2023
                : 51
                : 4
                : 1785-1802
                Affiliations
                [1 ] Department of Psychology Syracuse University Syracuse New York USA
                Article
                10.1002/jcop.22963
                d070a544-7ed2-46dd-ac7a-00345b1e7e87
                © 2023

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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