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Article details
Title
Individual socio-demographic factors and perceptions of the environment as determinants of inequalities in adolescent physical and psychological health: the Olympic Regeneration in East London (ORiEL) study
Published in
BMC Public Health, February 2015
DOI 10.1186/s12889-015-1459-1
Pubmed ID
Authors
Abstract

Populations living in urban areas experience greater health inequalities as well as higher absolute burdens of illness. It is well-established that a range of social and environmental factors determine these differences. Less is known about the relative importance of these factors in determining adolescent health within a super diverse urban context. A cross-sectional sample of 3,105 adolescent participants aged 11 to 12 were recruited from 25 schools in the London boroughs of Newham, Tower Hamlets, Hackney and Barking & Dagenham. Participants completed a pseudo-anonymised paper-based questionnaire incorporating: the Warwick-Edinburgh Mental Well-being Scale used for assessing positive mental well-being, the Short Moods and Feelings Questionnaire based on the DSM III-R criteria for assessment of depressive symptoms, the Youth-Physical Activity Questionnaire and a self-assessment of general health and longstanding illness. Prevalence estimates and unadjusted linear models estimate the extent to which positive well-being scores and time spent in physical/sedentary activity vary by socio-demographic and environmental indicators. Logistic regression estimated the unadjusted odds of having fair/(very)poor general health, a long standing illness, or depressive symptoms. Fully adjusted mixed effects models accounted for clustering within schools and for all socio-demographic and environmental indicators. Compared to boys, girls had significantly lower mental well-being and higher rates of depressive symptoms, reported fewer hours physically active and more hours sedentary, and had poorer general health after full adjustment. Positive mental well-being was significantly and positively associated with family affluence but the overall relationship between mental health and socioeconomic factors was weak. Mental health advantage increased as positive perceptions of the neighbourhood safety, aesthetics, walkability and services increased. Prevalence of poor health varied by ethnic group, particularly for depressive symptoms, general health and longstanding illness suggesting differences in the distribution of the determinants of health across ethnic groups. During adolescence perceptions of the urban physical environment, along with the social and economic characteristics of their household, are important factors in explaining patterns of health inequality.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Nigeria 1 <1%
United Kingdom 1 <1%
Unknown 246 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 49 20%
Student > Bachelor 25 10%
Researcher 22 9%
Student > Ph. D. Student 20 8%
Student > Doctoral Student 15 6%
Other 35 14%
Unknown 82 33%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 39 16%
Social Sciences 32 13%
Nursing and Health Professions 18 7%
Psychology 13 5%
Sports and Recreations 11 4%
Other 35 14%
Unknown 100 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 February 2015.
All research outputs
#26,276,529
of 32,890,663 outputs
Outputs from BMC Public Health
#17,090
of 20,609 outputs
Outputs of similar age
#318,264
of 426,054 outputs
Outputs of similar age from BMC Public Health
#196
of 245 outputs
Altmetric has tracked 32,890,663 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,609 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.9. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 426,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 245 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.