Lessons learned from building and analyzing multilevel data on the social capital-health relationship of women in fragile families /

It is recognized that multiple determinants of health, across multiple levels of influence, affect health status. Our previous research investigated the impact of social capital constructs of social support, social trust, social participation, and perceptions of neighborhood social cohesion and cont...

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Bibliographic Details
Main Authors: Dauner, Kim Nichols (Author), Wilmot, Neil A. (Author)
Format: eBook
Language:English
Published: London : SAGE Publications Ltd., 2020.
Series:SAGE Research Methods Cases : Medicine and Health.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:It is recognized that multiple determinants of health, across multiple levels of influence, affect health status. Our previous research investigated the impact of social capital constructs of social support, social trust, social participation, and perceptions of neighborhood social cohesion and control on health at the individual level. To capture aspects of social capital functioning at multiple levels--that is, individual and community levels--a multilevel construct was considered. Metropolitan religious adherence, which is a publicly available measure obtained from Social Explorer, an online database of demographic information, was adopted as the community-level measure of social capital. This community measure was then matched to individual women from a cohort study--the Fragile Families and Child Wellbeing--for which information on self-reported health and individual-level social capital and socioeconomic factors were obtained. This case focuses on the data acquisition process, and the building and analysis of the multilevel data. Specifically, we cover issues related to obtaining a data license for potentially identifiable data, and provide thoughtful consideration as to the characteristics of our data and our subsequent decision to use an ordered logistic regression with clustered standard errors to account for the multilevel nature of the data. Finally, we discuss the implications of our case in light of current challenges in public health research.
Physical Description:1 online resource.
Bibliography:Includes bibliographical references and index.
ISBN:9781529743388
1529743389