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The impact of social housing on mental health: longitudinal analyses using marginal structural models and machine learning-generated weights

Overview of attention for article published in International Journal of Epidemiology, June 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
3 news outlets
blogs
2 blogs
twitter
47 X users
wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Readers on

mendeley
109 Mendeley
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Article details
Title
The impact of social housing on mental health: longitudinal analyses using marginal structural models and machine learning-generated weights
Published in
International Journal of Epidemiology, June 2018
DOI 10.1093/ije/dyy116
Pubmed ID
Authors
Abstract

Social housing may provide an affordable and secure residential environment, but has also been associated with stigma, poor housing conditions and locational disadvantage. We examined the cumulative effect of additional years, and tenure security (number of transitions in/out), of social housing on mental health in a large cohort of lower-income Australians. We analysed a longitudinal panel survey that annually collected information on tenure and health from 2001 to 2013. To address the time-varying effect of previous health on social housing occupancy, we used marginal structural models. Stabilized inverse probabilities of treatment weights were generated using ensemble learning to improve prediction. To address remaining residual imbalance across covariates, double adjustment was made by additionally including baseline covariates in models. Mental health was measured using the Mental Health Short-Form summary measure of the SF-36 (MH), and psychological distress was measured using the Kessler Psychological Distress Scale (K10). People who had continuous exposure to social housing had worse mental health on average than people continuously occupying other tenures. The worst mental health outcomes, however, were observed for people who made multiple transitions. Mental health deteriorated and psychological distress increased with number of transitions: MH -1.04 [95% confidence interval (CI) -2.16; 0.09) and K10 0.56 (95% CI 0.12; 1.00). Estimates are in the order of 6% (MH) and 9% (K10) of one standard deviation for each measure. The more transitions people made in/out of social housing, the greater the impact on mental health and psychological distress, supporting the case for provision of more stable forms of social housing.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 47 X users 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 109 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 %
Unknown 109 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 17 16%
Researcher 10 9%
Lecturer 6 6%
Student > Doctoral Student 6 6%
Other 5 5%
Other 15 14%
Unknown 50 46%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 11 10%
Social Sciences 10 9%
Computer Science 5 5%
Psychology 5 5%
Nursing and Health Professions 4 4%
Other 12 11%
Unknown 62 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 68. 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 07 June 2023.
All research outputs
#756,649
of 32,463,143 outputs
Outputs from International Journal of Epidemiology
#352
of 6,401 outputs
Outputs of similar age
#12,828
of 362,865 outputs
Outputs of similar age from International Journal of Epidemiology
#5
of 83 outputs
Altmetric has tracked 32,463,143 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,401 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.1. This one has done particularly well, scoring higher than 94% of its peers.
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 362,865 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.