title: Pathways connecting neighborhood influences and mental well-being: socioeconomic position and gender differences.
abstract: Few studies have explored how participant socioeconomic position (SEP) and gender is related to perceptions of the pathways connecting neighborhood influences and mental well-being. This research used the concept mapping method, an intensive structured conceptualization process that produces pictorial views of how concepts are connected and interrelated. Thirty-six low and non-low SEP men and women from Toronto, Canada participated in the concept mapping sessions. One hundred and twenty unique neighborhood characteristics were felt to be related to mental well-being and those items were grouped into six distinct clusters. Notable differences in cluster importance by participant SEP status were found. While no overall differences were observed for males verses females, further stratification by both participant SEP and gender suggested that gendered perceptions are not uniform. Participant-created diagrams illustrated how the cluster domains are related to each other and to good mental well-being. These findings are important for uncovering the mechanisms by which neighborhoods differentially affect the mental health of residents from different SEPs and genders.
authors.affiliation: Behavioral and Community Health Sciences, University of Pittsburgh Graduate School of Public Health, 130 DeSoto Street, 218 Parran Hall, Pittsburgh, PA 15238, USA. jgburke@pitt.edu
authors.forename: Jessica
authors.initials: J
authors.lastname: Burke
authors.forename: Patricia
authors.initials: P
authors.lastname: O'Campo
authors.forename: Christina
authors.initials: C
authors.lastname: Salmon
authors.forename: Renee
authors.initials: R
authors.lastname: Walker
mesh_terms: D000328:Adult; D005260:Female; D015438:Health Behavior; D006304:Health Status; D006801:Humans; D007182:Income; D008297:Male; D008603:Mental Health; D009864:Ontario; D036301:Qualitative Research; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012923:Social Class; D012959:Socioeconomic Factors; D014505:Urban Population / Q000706:statistics & numerical data