2015
DOI: 10.1038/ijo.2015.98
|View full text |Cite
|
Sign up to set email alerts
|

Independent associations between child and parent perceived neighborhood safety, child screen time, physical activity and BMI: a structural equation modeling approach

Abstract: Findings indicate that targeting both parent and child perceived neighborhood safety could bolster efforts to promote healthy weight and weight-related behaviors among children.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
21
0

Year Published

2016
2016
2021
2021

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 22 publications
(22 citation statements)
references
References 52 publications
1
21
0
Order By: Relevance
“…From our logistic regression findings, we were interested in exploring potential mediating relationships between work organization characteristics, sleep outcomes, stress, and drivers’ perceptions of their sleep’s impact on work-life conflict. Although structural equation modeling (SEM) is typically conducted with longitudinal data and SEM with cross-sectional data cannot establish causal pathways, previous studies have effectively used SEM in post-hoc analyses involving cross-sectional data used for testing the directional associations between variables and the fit of a hypothesized model [65,66,67,68,69,70]. Based on the regression analyses, SEM was used to explore for potential mediating influences (Figure 2).…”
Section: Methodsmentioning
confidence: 99%
“…From our logistic regression findings, we were interested in exploring potential mediating relationships between work organization characteristics, sleep outcomes, stress, and drivers’ perceptions of their sleep’s impact on work-life conflict. Although structural equation modeling (SEM) is typically conducted with longitudinal data and SEM with cross-sectional data cannot establish causal pathways, previous studies have effectively used SEM in post-hoc analyses involving cross-sectional data used for testing the directional associations between variables and the fit of a hypothesized model [65,66,67,68,69,70]. Based on the regression analyses, SEM was used to explore for potential mediating influences (Figure 2).…”
Section: Methodsmentioning
confidence: 99%
“…Finally, built environment involved 12 variables: air quality and pollution, 92 , 93 creative or supportive environment, 94 designing smart cities, 36 geographic transportation, 90 , 95 , 96 greenness, 55 , 97 , 98 physical activity, 39 policymaking perspectives, 99 , 100 , 101 , 102 promotion, 103 , 104 residential density, 105 risk of injury, 40 , 49 safety, 106 , 107 and travel distance, duration, and destination. 47 , 50 , 106 , 107 Although the majority of Canadian studies on EFHL analyzed can be divided into these 4 categories, discussions of other issues—smoking, for example—are totally absent or negligible. 108 , 109…”
Section: Resultsmentioning
confidence: 99%
“…The social ecological model of PA ( Sallis et al, 2006 ) posits that behavior is influenced by both individual-level characteristics, such as gender, and by multiple dimensions of the context within which the behavior takes place, including family, peers, and physical environment. Evidence for this model comes from studies showing that some portion of PA participation among adolescents may be attributed to socioeconomic status ( Elgar et al, 2015 ), perceived neighborhood safety ( Cote-Lussier et al, 2015 ), and/or proximity of recreational resources ( Carroll-Scott et al, 2013 ). Moreover, there may be cross-level interactions, for example between gender and environmental factors, that generate disparities in activity across gender.…”
Section: Discussionmentioning
confidence: 99%